Medical module including automated dose-response record system

ABSTRACT

An automated dose-response record system including a module for housing waste-heat producing electronic and electromechanical medical equipment including at least one physiologic monitor, and including a system to measure, temporally correlate and record dose and response events.

PRIORITY

This application is a continuation of U.S. patent application Ser. No.17/245,942, filed Apr. 30, 2021, which is a continuation-in-part of U.S.patent application Ser. No. 17/167,681, filed Feb. 4, 2021, which is acontinuation-in-part of U.S. application Ser. No. 17/092,681, filed Nov.9, 2020, now U.S. Pat. No. 10,993,865, which is a continuation of U.S.patent application Ser. No 16/879,406, filed May 20, 2020, now U.S. Pat.No. 10,869,800. The disclosure of all of these applications areincorporated herein by reference in their entirety.

TECHNICAL FIELD

This document pertains generally, but not by way of limitation, tosystems and methods for improving safety in operating rooms. Inparticular, the systems and methods described herein may include but arenot limited to, anesthetic and surgical equipment storage andoperational data capture, automated anesthetic and patient monitoringdata capture and electronic record input.

BACKGROUND

Anesthesia monitors and equipment as well as surgical equipment havebeen invented, developed and sporadically introduced into surgicalpractice over more than a century. This equipment is made by a widevariety of companies who have no incentive to coordinate with oneanother to create the most efficient operating room. Equipmentthroughout the operating room has been placed in one location oranother, generally without a plan and then decades later, is stillsitting in that unplanned location.

Over the past 20 years, there has been a gradual movement to replacingpaper anesthetic records with electronic anesthetic records (EAR).However, the identity, dosing and timing of IV and inhaled drugadministration, IV fluid administration, oxygen and ventilation gasadministration and anesthetic events such as intubation have requiredmanual input to the EAR by way of a computer keyboard and mouse. Blood,fluid and urine outputs have also required manual input to the EAR byway of a computer keyboard and mouse. The surgical equipment scatteredaround the operating room either does not produce a digital output thatcould memorialize the equipment's operation to the electronic record,that output is not automatically captured, or the output is not providedin a way that provides meaningful context or correlation.

Carefully observing the patient in various conditions and situationsincluding surgery is a source of medical information. However, in thisage of electronic monitoring, patient observation by the healthcareprovider is becoming a lost art that is infrequently done and if it isdone it may not be entered into the record so the information is lost.

SUMMARY

As a result of the current medical practices described, the majority ofthe input to the electronic anesthetic and medical records has been thedata from the vital signs monitors, recording the patient's “response.”The “dose” events (things that are given or done to the patient leadingto the “response”) are manually entered into the record, resulting inmistakes, omissions and no temporal correlation between the dose andresponse. The incomplete and inaccurate records make any analysis withartificial intelligence and machine learning software problematic,either for that individual patient or for “big data” analysis ofpopulations of patients.

This document pertains generally to systems and methods for improvingsafety for patients receiving intravenous (IV) medications and fluids,by avoiding medication or fluid errors and documenting theadministration. This document pertains generally, but not by way oflimitation, to systems and methods for constructing granular(beat-by-beat) anesthetic, surgical and patient records that includeboth “dose” events (things that are given or done to the patient) and“response” events (inputs from electronic monitors, measurement devicesand machine vision “observations”). The dose and response events areprecisely temporally related and recorded in the patient's electronicrecord and may be pooled with the records of other patients in adatabase that can be analyzed with artificial intelligence and machinelearning software.

Illustrative examples of an automated dose-response record system thatsystematizes surgical safety for patients and OR personnel. In someexamples, this automated dose-response record system is designed tohouse nearly all of the operating room patient monitors and supportequipment. Even dissimilar types of equipment that are normally keptseparate from one another. In some examples, this unique automateddose-response record system is specially designed to fit next to andunder the arm-board of the surgical table—a location traditionallyoccupied by an IV pole. For the past 100 years, this location has been awasted “no-man's land” between the anesthesia and surgical sides of theoperating room. In reality, the unique space next to and under thearm-board, is truly the “prime real estate” of the entire operatingroom: it is immediately adjacent the patient for optimal monitoringwhile simultaneously maintaining observation of the patient and surgicalprocedure; equipment controls can be conveniently accessed by both theanesthesia and surgical staff; short cables and hoses are adequate toreach the patient; and it is uniquely accessible from both theanesthesia and surgical sides of the anesthesia screen. The unique spacenext to and under the arm-board is the only location in the entireoperating room where cables, cords and hoses from both the anesthesiaside and the sterile surgical field side, do not need to traverse thefloor or even touch the floor in order to connect to their respectivemonitor or patient support equipment truly a remarkable location thathas been wasted by conventional systems.

In some examples, an illustrative automated dose-response record systemcan house both anesthesia related and non-anesthesia related equipment.In some examples, the illustrative relocation module can house a varietyof non-proprietary OR equipment such as patient vital sign monitors,electro-surgical generators, anesthesia machines and mechanicalventilators. In some examples, the automated dose-response record systemis designed to also house newer proprietary safety equipment such as:air-free electric patient warming, surgical smoke evacuation, wastealcohol and oxygen evacuation, evacuation of the flow-boundarydead-zones that cause disruption of the OR ventilation and theevacuation and processing of waste heat and air discharged from ORequipment. In some examples, this automated dose-response record systemmay also house dissimilar equipment (e.g., unrelated to anesthesiamonitoring) such as: air mattress controls and air pumps; sequentialcompression legging controls and air pumps; capacitive couplingelectrosurgical grounding; RFID counting and detection of surgicalsponges; the waste blood and fluid disposal systems; and “hover”mattress inflators. Any of these devices may be stored in the automateddose-response record system together with (or without) anesthesiaequipment.

In some examples, the automated dose-response record system is aspecialized and optimally shaped rack for holding and protecting thepatient monitors and other electronic and electromechanical surgicalequipment, in a unique location. A location that is very different fromjust setting anesthesia monitors on top of the anesthesia machine andscattering other equipment across the floor of the operating room.

The various pieces of electronic and electromechanical equipment housedwithin the automated dose-response record system disclosed herein canproduce relatively large amounts of waste heat. The bulbous lowersection of the module is placed on the floor next to the surgical tableand is below table height since it is under the arm-board. Releasingwaste heat in this location on the floor next to the surgical table maycause a risk of sterile field contamination from the rising waste heatthat may include squames and other contaminants. In some examples, theautomated dose-response record system may include a waste heatmanagement system to safely dispose of the waste heat created by theelectronic and electromechanical equipment housed within the automateddose-response record system.

It would be difficult or even impossible to manage the uncontained wasteheat produced by electronic and electromechanical equipment mounted on asimple open rack because it can escape in any direction. In someexamples, the module can include a “cowling” covering substantially theentire outer or inner surface. The cowling not only protects theequipment from accidental fluid damage but also confines the waste heatfrom the electronic and electromechanical equipment mounted within themodule, to the inside of the module and cowling. In some examples, theconfined waste heat can then be safely managed.

In some examples, the cowling cover of the automated dose-responserecord system can form or support a waste heat management system. Insome examples, the cowling can be provided on an inner surface of thehousing. In some examples, the cowling can be described as aninsulation. In some examples, the housing can include other types ofinsulation from heat and/or water. Any suitable type of insulatedhousing suitable for use in a surgical field can be provided.

In some examples, the automated dose-response record system of theinstant invention may also contain the components of the anesthesia gasmachine. So-called “gas machines” are relatively simple assortments ofpiping, valves, flow meters, vaporizers and a ventilator. These could belocated within the automated dose-response record system or attached tothe automated dose-response record system for further consolidation ofequipment and for improved access to the patient. The close proximity tothe patient not only shortens the ventilation tubing but also shortensthe sampling tubing for the carbon dioxide monitor. The close proximityof the anesthesia gas machine to the patient also allows continuousobservation of the patient while adjusting the gas and anesthetic flows.

In some examples, locating the anesthesia machine in or on the automateddose-response record system allows direct access for and sensors andmonitors related to the anesthesia machine, to input data to theelectronic anesthetic record being recorded by equipment in theautomated dose-response record system.

In some examples, an illustrative automated dose-response record systemcan house both anesthesia related and non-anesthesia related equipment.In some examples, the illustrative automated dose-response record systemcan house a variety of non-proprietary OR equipment such as patientvital sign monitors and electro-surgical generators. In some examples,the automated dose-response record system is designed to also housenewer proprietary safety equipment such as: air-free electric patientwarming, surgical smoke evacuation, waste alcohol and oxygen evacuation,evacuation of the flow-boundary dead-zones that cause disruption of theOR ventilation and the evacuation and processing of waste heat and airdischarged from OR equipment. In some examples, this automateddose-response record system may also house dissimilar equipment (e.g.,unrelated to anesthesia monitoring) such as: air mattress controls andair pumps; sequential compression legging controls and air pumps;capacitive coupling electrosurgical grounding; RFID counting anddetection of surgical sponges; the waste blood and fluid disposalsystems; and “hover” mattress inflators. Any of these devices may bestored in the automated dose-response record system together with (orwithout) anesthesia equipment and be in electrical communication withprocessing circuitry of the dose-response system.

In some examples, the automated dose-response record system is aspecialized and optimally shaped rack for holding and protecting thepatient monitors and other electronic and electromechanical surgicalequipment, in a unique location. A location that is very different fromjust setting anesthesia monitors on top of the anesthesia machine andscattering other equipment across the floor of the operating room.

In some examples, the collection canisters for waste fluid and blood maybe conveniently mounted on the module. Mounting the canisters on theautomated dose-response record system eliminates the need for vacuumtubing to lay on the floor while traversing from the wall outlet to thecanister and from the surgical field to the canister. Optical orinfrared fluid level sensors 153 may be conveniently mounted in themodule, adjacent the canister(s). In some examples, the fluid levelmonitors may automatically activate or deactivate the vacuum to a givencanister, thereby automatically shifting the blood and fluid flow to anew canister as the previous one is filled.

In some examples, the controls and display screens for the surgicalequipment housed in the automated dose-response record system may bewirelessly connected to a portable display screen such as an iPad or“smart tablet,” for convenient access by the nurse anywhere in the room.This allows the surgical nurse to monitor and control the equipmentwithout walking across the room. This is convenient for the nurse andincreases awareness of equipment conditions. Staff moving around the ORkick up contaminates from the floor into the air where they can becarried to the sterile surgical field by waste heat. A portable displayscreen minimizes surgical staff movement in the OR which has been shownto reduce airborne contamination and surgical site infections.

Doctors and nurses dislike record keeping and the switch to theelectronic record has made the act of record keeping more difficult andtime consuming. Entering the electronic record into the computersometime after the event occurred and the case has settled down, is notonly distracting from patient care but leads to inaccurate records. Handentered records also bypass the opportunity for the computer to add topatient safety by checking drug identities, dosages, side effects,allergies and alerting the clinician to potential problems or evenphysically stopping the drug administration. Manually entered recordsare not useful for managing drug inventories because a given medicationadministration is not tied to a specific drug bottle or syringe.Finally, the computer mouse and keyboards have been shown to becontaminated by a wide variety of infective organisms and are virtuallyimpossible to clean. Automatic anesthetic data entry to the EAR wouldimprove patient safety, improve clinician job satisfaction and improveOR inventory management.

In general, doctors and nurses are not interested in replacingthemselves and their jobs with automated drug delivery or automatedanesthesia systems. However, they may be more open to automated recordkeeping. The challenge with automated record keeping is automating thedata input that documents the numerous activities, anesthesia relatedevents, fluid, gas and medication administration that constitute ananesthetic experience or another medical situation

The second challenge in implementing an automated electronic anestheticrecord (EAR) or electronic medical record (EMR) is to force as littlechange in routine as possible onto the anesthesiologist and otherclinicians using this system. Anesthesiologists and surgeons aregenerally tradition-bound and resistant to any changes in their “triedand true” way of doing things. Therefore, a successful automated EARshould interact seamlessly with current anesthesia practices andoperating room workflow without causing any disruptions.

In some examples, the automated EAR of this disclosure includes a systemfor automatically measuring and recording the administration of IVmedications and fluids. The system for automatically measuring andrecording the administration of IV medications and fluids can includeone or more sensors, such as one or more of a barcode reader and an RFIDinterrogator for accurately identifying a medication or fluid for IVadministration.

The system for automatically measuring and recording the administrationof IV medications and fluids can also include one or more digitalcameras with machine vision software (“machine vision”) for accuratelymeasuring the volume of medication administered from a syringe or fluidadministered from an IV bag through a drip chamber into an IV tubing.The digital cameras with machine vision software basically duplicate theclinician's vision of an activity, injection of a drug from a syringefor example, without interfering in the normal activity and yet allowsautomatic recording of the activity in the EAR. The machine visionsoftware can include one or more machine-readable mediums that whenimplemented on hardware processing circuitry of the system or inelectrical communication with the system, can perform the functionsdescribed herein.

In some examples, the automated EAR of this disclosure uses machinevision to unobtrusively “observe” the flow rate of the ventilation gasflow meters and inhaled anesthetic vaporizers.

In some examples, the automated EAR of this disclosure captures inputdata from the blood and fluid collection and urine output collectionsystems (e.g., 242) of this disclosure.

In some examples, a system for automatically measuring and recording theadministration of IV medications and fluids can also include, or caninstead include, one or more digital cameras with machine visionsoftware (“machine vision”) for accurately measuring the volume ofmedication administered from a syringe or fluid administered from an IVbag through a drip chamber into an IV tubing. The digital cameras withmachine vision software basically duplicate the clinician's vision of anactivity, injection of a drug from a syringe for example, withoutinterfering in the normal activity and yet allows automatic recording ofthe activity in the EMR. The machine vision software can include one ormore machine-readable mediums that when implemented on hardwareprocessing circuitry of the system or in electrical communication withthe system, can perform the functions described herein.

In some examples, the automatic EMR of the security system for IVmedications of this disclosure lets the computer (e.g., a processor andmemory for performing instructions) add to patient safety by checkingdrug identities, dosages, side effects, allergies, the patients' medicalhistory and vital signs and alerting the clinician to potential problemsor even physically stopping the drug administration. In some examples,the automatic EMR of this disclosure eliminates medication errors bychecking the drug to be injected against the physician's medicationorders before the injection can occur. In some examples, the automaticEMR of this disclosure is useful for managing drug inventories because agiven medication administration is tied to a specific drug bottle orsyringe. Finally, the computer mouse and keyboards have been shown to becontaminated by a wide variety of infective organisms and are virtuallyimpossible to clean. Automatic data entry to the EMR would improvepatient safety, improve clinician job satisfaction and improvemedication inventory management.

In some examples, the automatic EMR of the security system for IVmedications of this disclosure may also automatically record and displaymany other functions including but not limited to: IV fluidadministration, medication infusions, the patient's vital signs, urineoutput, blood loss, ventilator settings, inspired gases, electrosurgicalsettings, pneumoperitoneum insufflation settings, RFID surgical spongecounts, surgical information and video, dialysis or other medicalprocedure information and patient activity.

The art and science of medicine can include giving something to thepatient (a medicine for example) or doing something to the patient(mechanical ventilation or surgery for example)—the “dose”, and thenobserving the patient's “response.” The problem now seen with electronicrecords is that the only data that is timely recorded is the “response”data provided by the physiologic monitors. Even that response data isfrequently not recorded beat-by-beat but rather intermittently recordedevery 5 minutes or 30 minutes or 4 hours for example. All of the “dose”data is entered into the electronic record by hand and therefore isprone to mistakes, omissions and unknown timing. Therefore, with currentEMRs, the dose and response data cannot be temporally correlated withany accuracy, vastly reducing the analytical and predictive value of theelectronic database and record.

In some examples, the automatic EMR of the security system for IVmedications of this disclosure includes systems and methods forconstructing granular (beat-by-beat, second-by-second) anesthetic,surgical and patient records that include both “dose” events—the thingsthat are given or done to the patient (inputs from medication injectionand fluid monitors, various support equipment and machine vision“observations” for example) and “response” events (inputs fromelectronic monitors, measurement devices and machine vision“observations” for example). In some examples, the invention of thisdisclosure automatically enters both dose and response events into theelectronic record. In some examples, the invention of this disclosureautomatically enters both dose and response events into the electronicrecord and temporally correlates the dose and response events, such asbut not limited to, when they are recorded. In some examples, theautomatically entered, temporally correlated dose and response events inthe patient's electronic record may be analyzed by artificialintelligence (AI) and/or machine learning (ML) software stored in amemory of a storage device electrically coupled to the processingcircuitry of the module for immediate advice, alerts and feedback to theclinician. In some examples, the automatically entered, temporallycorrelated dose and response events in the patient's electronic recordmay be pooled with the records of other patients in a database that canbe analyzed with artificial intelligence and machine learning software.

Machine Learning (ML) is an application that provides computer systemsthe ability to perform tasks, without explicitly being programmed, bymaking inferences based on patterns found in the analysis of data.Machine learning explores the study and construction of algorithms(e.g.,tools), that may learn from existing data and make predictions about newdata. Such machine-learning algorithms operate by building an ML modelfrom example training data in order to make data-driven predictions ordecisions expressed as outputs or assessments. The principles presentedherein may be applied using any suitable machine-learning tools.

In some examples, the AI or ML software can compare dose and responseevents from different periods of time for the same patient to learn andidentify the particular patient's responses. In some examples themachine learning software can be trained to identify a patient'sresponses using training obtained from a one or more patients that mayinclude or not include the patient being monitored. Any suitable AI orML can be implemented to interpret the data generated by the module.Current methods of obtaining data in medical settings cannot generate,store or aggregate such data for analysis using AI or ML. Thus, thedose-response systems described herein provide a technical solution to atechnical problem.

Machine vision cameras and software are very good at measuringdistances, movements, sizes, looking for defects, fluid levels, precisecolors and many other quality measurements of manufactured products.Machine vision cameras and software can also be “taught” through AI andML to analyze complex and rapidly evolving scenes, such as those infront of a car driving down the road.

In some examples, the automatic EMR of the security system for IVmedications of this disclosure includes novel systems and methods forusing machine vision cameras and software to “observe” the patient. Ifthe patient is in surgery, the patient's head may be the focus of theobservation. In some examples, during surgery the machine vision camerasand software may be “looking” for dose events including but not limitedto mask ventilation or endotracheal intubation. In some examples, duringsurgery the machine vision cameras and software may be “looking” forresponse events including but not limited to grimacing or tearing orcoughing or changes in skin color.

If the patient is on the ward or in the nursing home or other long-termcare facility, the whole patient may be the focus of the observation. Insome examples, if the patient is on the ward or in the nursing home orother long-term care facility the machine vision cameras, processingcircuitry and software may be configured to “look” for dose events(e.g., sense, detect, monitor) including but not limited torepositioning the patient, suctioning the airway or assisting thepatient out of bed or any other nursing procedure. In some examples, ifthe patient is on the ward or in the nursing home or other long-termcare facility (including at home) the machine vision cameras, processingcircuitry and software may be configured to “look” for response events(e.g., sense, detect, monitor) including but not limited to restlessnessor getting out of bed without assistance or coughing or breathingpattern. In some examples, the system can go beyond traditionalphysiologic monitors. Even physiologic response information such as painmay be detected by facial expression analysis.

In some examples, vital signs such as heart rate, respiration rate,blood oxygen saturation and temperature can be measured (e.g., sensed,detected, monitored) remotely via camera-based methods. Vital signs canbe extracted from the optical detection of blood-induced skin colorvariations—remote photoplethysmography (rPPG).

In some examples, the automatic EMR of the security system for IVmedications may allow remote viewing of the displayed patientinformation. In some examples, the remotely displayed patientinformation may be used for remote medical supervision such as ananesthesiologist providing remote supervision to a nurse anesthetist whois administering the anesthetic. In some examples, the remotelydisplayed patient information may be used for remote medicalconsultation. In some examples, the remotely displayed patientinformation may be used to document the involvement of remote medicalsupervision or consultation for billing purposes.

BRIEF DESCRIPTION OF THE DRAWINGS

In the drawings, which are not necessarily drawn to scale, like numeralsmay describe similar components in different views. Like numerals havingdifferent letter suffixes may represent different instances of similarcomponents. The drawings illustrate generally, by way of example, butnot by way of limitation, various examples discussed in the presentdocument. Any combination of the features shown and described in thisdisclosure, including combinations of fewer or more features is withinthe content of this disclosure. Modules, systems and methods includingindividual features described herein, without combinations of featuresas shown in the examples (for the sake of brevity), are also within thescope of this disclosure.

FIG. 1 illustrates an isometric view of an example module including asystem for generating an automated electronic anesthetic record locatedproximate to a patient, in accordance with at least one example of thisdisclosure.

FIG. 2 illustrates an isometric view of an example module including asystem for generating an automated electronic anesthetic record locatedproximate to a patient, in accordance with at least one example of thisdisclosure.

FIG. 3 illustrates a plan view of an example of preloaded syringes thatcan be used with the system of FIGS. 1 and 2, in accordance with atleast one example of this disclosure.

FIG. 4 illustrates a side view of an example medication identificationand measurement system and a syringe that can be used with the system ofFIGS. 1 and 2, to monitor drug delivery, in accordance with at least oneexample of this disclosure.

FIG. 5 illustrates a cross-sectional view of the medicationidentification and measurement system and a syringe (not shown incross-section) of FIG. 4, taken along line 5-5, in accordance with atleast one example of this disclosure.

FIG. 6 illustrates a side view of a second example medicationidentification and measurement system and a syringe that can be usedwith the system of FIGS. 1 and 2, in accordance with at least oneexample of this disclosure.

FIG. 7 illustrates a cross-sectional view of the second example of amedication identification and measurement system and the syringe (notshown in cross-section) of FIG. 6, taken along line 7-7, in accordancewith at least one example of this disclosure.

FIG. 8 illustrates a side view of a third example of a medicationidentification and measurement system and a syringe that can be usedwith the system of FIGS. 1 and 2, in accordance with at least oneexample of this disclosure.

FIG. 9 illustrates a cross-sectional view of the third example of amedication identification and measurement system and the syringe (notshown in cross-section) of FIG. 8, taken along line 9-9, in accordancewith at least one example of this disclosure.

FIG. 10 illustrates an example injection port cassette that can be usedwith the system of FIGS. 1 and 2, as detailed in FIGS. 5, 7 and 9, inaccordance with at least one example of this disclosure.

FIG. 11 illustrates a plan view of an example of healthcare provider IDbadges that can be used with the system of FIGS. 1 and 2, in accordancewith at least one example of this disclosure.

FIG. 12 illustrates an isometric view of another example moduleincluding a system for generating an automated electronic anestheticrecord located proximate to a patient, in accordance with at least oneexample of this disclosure.

FIG. 13 illustrates an isometric view of another example moduleincluding a system for generating an automated electronic anestheticrecord located proximate to a patient, in accordance with at least oneexample of this disclosure.

FIG. 14 illustrates a side view of an example IV fluid identificationand measurement system that can be used with the systems of FIGS. 1 and2, and injection port cassette of FIG. 10, in accordance with at leastone example of this disclosure.

FIG. 15 illustrates generally an example of a block diagram of a machine(e.g., of module 101, 201) upon which any one or more of the techniques(e.g., methodologies) discussed herein may perform in accordance with atleast one example of this disclosure.

FIG. 16 is a flow chart illustrating a technique of IV fluididentification and measurement, in accordance with at least one exampleof this disclosure.

FIG. 17 is a second flow chart illustrating the technique of IV fluididentification and measurement, in accordance with at least one exampleof this disclosure.

FIG. 18 is a flow chart illustrating a technique of medicationidentification and measurement, in accordance with at least one exampleof this disclosure.

FIG. 19 is a second flow chart illustrating a technique of medicationidentification and measurement, in accordance with at least one exampleof this disclosure.

FIG. 20 is a flow chart illustrating a second technique of IV fluididentification and measurement including safety and security aspects, inaccordance with at least one example of this disclosure.

FIG. 21 is a second flow chart illustrating a second technique of IVfluid identification and measurement including safety and securityaspects, in accordance with at least one example of this disclosure.

FIG. 22 illustrates generally an example of a block diagram of vendingsystem and a medication delivery system of FIGS. 1-21 upon which any oneor more of the techniques (e.g., methodologies) discussed herein mayperform in accordance with at least one example of this disclosure.

FIG. 23 is a flow chart illustrating a technique 2300 for assessingphysiologic events, in accordance with at least one example of thisdisclosure.

FIG. 24 is a flow chart illustrating a technique 2400 for temporallycorrelating and analyzing dose-response events, in accordance with atleast one example of this disclosure.

DETAILED DESCRIPTION

The following detailed description is exemplary in nature and is notintended to limit the scope, applicability, or configuration of theinvention in any way. Rather, the following description providespractical illustrations for implementing exemplary examples of thepresent invention. Examples of constructions, materials, dimensions, andmanufacturing processes are provided for selected elements, and allother elements employ that which is known to those of skill in the fieldof the invention. Those skilled in the art will recognize that many ofthe examples provided have suitable alternatives that can be utilized.

As described herein, operably coupled can include, but is not limitedto, any suitable coupling, such as a fluid (e.g., liquid, gas) coupling,an electrical coupling or a mechanical coupling that enables elementsdescribed herein to be coupled to each other and/or to operate togetherwith one another (e.g., function together).

Dose-response involves giving something to the patient (a medicine forexample) or doing something to the patient (mechanical ventilation orsurgery for example)—the “dose”, and then observing the patient's“response.”

Throughout this disclosure, the word “dose” or “dose event” meanssomething that was given to or done to the patient. In some examples,“dose events” involve giving something to the patient including but notlimited to: the injection or ingestion of medications, the infusion ofmedications, the infusion of IV fluids, inspired gases such as oxygen ornitrous oxide or volatile anesthetics or nitric oxide.

In some examples, “dose events” are things done to the patient,including but not limited to: mask ventilation, tracheal intubation,mechanical ventilation, pneumoperitoneum insufflation, patientpositioning and surgery.

In some examples, “dose events” are applications of electricity to thepatient, including but not limited to: train-of-four determination ofmuscle relaxation, nerve conduction studies, cardiac pacing,cardioversion, electrical stimulation of nerves and electroconvulsivetherapy. Many other “dose events” are anticipated.

Throughout this disclosure, the word “response” or “response event”means a physiologic, reflexive motor response or volitional motorresponse from the patient. In some examples, “response events” involvemeasuring a physiologic response of the patient measured by thephysiologic monitors (e.g., 270 or others), including but not limitedto: an electrocardiogram (EKG), pulse oximetry, blood pressure, endtidal gases, electroencephalogram (EEG), bispectral index (BIS),laboratory blood studies, urine output (e.g., 242), blood loss andpulmonary compliance.

In some examples, “response events” involve measuring a motor responseof the patient, including but not limited to: a train-of-four,grimacing, coughing, movements of many sorts and tearing that may becaptured to detect by a machine vision camera in conjunction withsoftware (e.g., 1297A, 1297B, 1397 such as described in at least FIGS.12, 13 and 15).

FIG. 1 illustrates an isometric view of an example automateddose-response record system 100 for generating an automated electronicanesthetic record (EAR) or electronic medical record (EMR) locatedproximate to a patient. Some aspects of FIG. 1 are also described withrespect to the description of other figures, including FIG. 14.

As shown in FIG. 1, the automated dose-response record system 100 may beattached to and portions can be stored within a module 101. The module101 can conveniently provide direct access to the patient 102. An IVpole 105 may provide a convenient mounting support location for theautomated dose-response record system for IV medications 100(hereinafter, “automated dose-response record system 100”). In someexamples, the components and systems of the automated dose-responserecord system 100 of this disclosure can be supported by other mountingsupports, including but not limited to a boom-mounted rack system, awheeled rack system and a bed 103 mounting bracket. One or morecomputers including processing circuitry 157, of the automateddose-response record system 100 of this disclosure may be convenientlyand safely housed inside the module 101.

In some examples, it is anticipated that some or all of the componentsof the automated dose-response record system 100 of this disclosurecould be used in other healthcare settings such as the intensive careunit, the emergency room or on the ward. As shown in FIG. 1, the module101 may be mounted on an IV pole 105 or other suitable mountingstructure located near the patient 102.

In some examples, a touch-screen electronic record display 126 canconvert to a qwerty-type keyboard to allow uncommon anesthetic andsurgical events or deviations from pre-recorded scripts, to be manuallydocumented. This allows the standard computer keyboard that is used fordata entry in most electronic anesthetic records, to be eliminated.Standard keyboards are known to be contaminated with pathogenicorganisms and are nearly impossible to clean and decontaminate due totheir irregular surfaces. In contrast, the smooth glass or plastic faceof a touch-screen monitor is easy to clean with no crevasses to hideorganisms.

In some examples, the automated dose-response record system for IVmedications 100 of this disclosure can include a system forautomatically measuring and recording the administration of IVmedications. In some examples, the system for automatically measuringand recording the administration of IV medications includes a medicationidentification and measurement system 128. In some examples, aspects ofthe automated dose-response record system 100 can be provided togetherwith or separately from other aspects of the IV medicationidentification and measurement system 128 (hereinafter, “medicationidentification and measurement system 128”). Likewise, aspects of themedication identification and measurement system 128 can be providedtogether with or separately from other aspects of the automateddose-response record system 100.

FIG. 2 illustrates an isometric view of an example automateddose-response record system 200 for generating an automated electronicanesthetic record located proximate to a patient 202. Features of theautomated dose-response record system 100 of FIG. 1 may be included inthe automated dose-response record system 200 of FIG. 2, and vice-versa,therefore all aspects may not be described in further detail. Likenumerals can represent like elements. Aspects of FIGS. 1 and 2 may alsobe described together. Some aspects of FIG. 2, including an IV fluididentification and measurement system 130, are described with respectother figures, including the description of IV fluid identification andmeasurement system 1430 of FIG. 14.

As shown in FIG. 2, an example medication identification and measurementsystem 228 may be attached to a relocation module 201 that may beadvantageously positioned proximate the patient 202, such as near thepatient's head on a surgical table 212. In this position medications canbe conveniently administered by medical personnel while also tending toand observing the patient 202 during surgery.

It would be difficult or even impossible to manage the uncontained wasteheat produced by electronic and electromechanical equipment mounted on asimple open rack because it can escape in any direction. In someexamples, the automated dose-response record system 100,200 can includea cowling (e.g., 299C; FIG. 2) covering substantially the entire outeror inner surface of the housing 299. The cowling 299C not only protectsthe equipment from accidental fluid damage but also confines the wasteheat from the electronic and electromechanical equipment mounted withinthe automated dose-response record system 100,200 to the inside of themodule 201 and cowling 299C. In some examples, the confined waste heatcan then be safely managed.

In some examples, the cowling 299C cover of the automated dose-responserecord system 100,200 can form or support a waste heat managementsystem. In some examples, the cowling 299C can be provided on an innersurface of the housing 299. In some examples, the cowling 299C can bedescribed as an insulation. In some examples, the housing 299 caninclude other types of insulation from heat and/or water. Any suitabletype of insulated housing 299 suitable for use in a surgical field canbe provided.

In some examples, the medication identification and measurement system128 (FIG. 1), 228 (FIG. 2) may include one or more sensors, such as oneor more of: a barcode reader or QR code reader (e.g., 436, FIG. 4), aradio-frequency identification (RFID) interrogator (e.g., 438, FIG. 4),or any other suitable sensor for accurately and reliably identifying amedication for IV administration. As defined herein, a barcode readercan include any other type of identifying reader, such as, but notlimited to, a QR code reader. Likewise, the RFID interrogator can be anytype of interrogator and is not limited to those interrogators based onradio frequency. Examples of such sensors are described herein, such asin FIGS. 4 and 5.

In some examples, instead of, or in addition to one or more of an RFIDinterrogator 438 and a barcode reader 436, the medication identificationand measurement system 128, 228 can receive an input to determine theidentity. For example, the medication identification and measurementsystem 128, 228 can include one or more of: a sensor, such as barcodereader 436 of FIG. 4, configured to identify the one or more IVmedications or fluids, or an input configured to receive the identity ofthe one or more IV medications or fluids, such as via the anestheticrecord input component 224.

In some examples, the barcode reader (e.g., 436, FIG. 4) may be a“computer vision” or “machine vision” camera with the capability ofreading barcodes. The term “machine vision” is often associated withindustrial applications of a computer's ability to see, while the term“computer vision” is often used to describe any type of technology inwhich a computer is tasked with digitizing an image, processing the datait contains and taking some kind of action. In this disclosure the terms“machine vision” and “computer vision” may be used interchangeably. Insome examples, multiple machine vision camera's can be used to performvarious functions described herein. Traditionally, machine visionincludes technology and methods used to provide imaging-based automaticinspection and analysis, process control, and robot guidance. Machinevision is sometimes used in manufacturing environments. Machine visionrefers to many technologies, software and hardware products includingprocessing circuitry, integrated systems and methods.

The inventors have discovered that machine vision can be useful beyondits traditional uses. The inventors discovered that machine vision canbe advantageous in implementing an automated dose-response record system100, 200 because it offers reliable measurements, gauging, objectrecognition, pattern recognition and liquid fill level measurements.Machine vision does not get tired or distracted. Machine vision excelsat quantitative measurement of a structured scene because of its speed,accuracy and repeatability. However, it does require the scene to bestructured to perform the desired function.

Machine vision can be very accurate for measuring size of an object at aknown distance or the distance of an object of known size. However, itcannot do both. Therefore, in some examples it is important to know theexact location of a syringe (e.g., 406, FIG. 4) and thus know thedistance from the camera (e.g., 436, FIG. 4) to the syringe (e.g., 406,FIG. 4) in order for the machine vision to calculate the distance of themovement of the plunger (e.g., 446, FIG. 5) within the syringe (e.g.,406, FIG. 5). This is what we mean by the “scene being structured.”

Machine vision may be advantageous for the automated dose-responserecord system 100, 200 of this disclosure because it “sees” andmeasures, but does not touch or interfere with the healthcare providerdoing their normal job of injecting medications or administering IVfluids. Further, the same visual image that is used by the machinevision software can be transmitted and displayed on a screen 126, 226 togive the operator (whose fingers can be pushing the plunger 446 of thesyringe 406, a close-up view of the syringe 406. FIG. 5 is across-section view taken at 5-5 of FIG. 4. The machine vision camera 436can be looking at the same view of the syringe 406 as the operator andit is the same or similar view that the operator would see if they wereinjecting IV medications the traditional way.

The machine vision camera, or digital camera, can include machine visionsoftware, or the machine vision camera can be in electricalcommunication with (e.g., operably coupled to) one or more hardwareprocessors, such as processing circuitry 157, 257 and one or moremachine-readable mediums 159, 259. The one or more machine-readablemediums 159, 259 can include instructions (e.g., software), that whenimplemented on the processing circuitry 157, 257, can perform thefunctions described herein. The processing circuitry 157, 257 can bestored in the module 101, relocation module 201 or remote from themodules 101, 201 (e.g. in a wired or wireless manner). The one or moremachine-readable mediums 159 can be a storage device, such as a memorylocated in the module 201 or remote from the module 101, 201.

In some examples, the RFID interrogator 438 may be either High Frequency(HF) or Near Field (NF) RFID in order to advantageously limit theread-range to a distance of less than 12 inches. In some examples, theRFID read-range may advantageously be limited, such as to less than 8inches so that only a specific medication injection is identified at anytime. In a possibly more preferred example, the RFID read-range may belimited to less than 4 inches to further prevent mis-readings. NF-RFIDhas a short read-range by definition and the read-range of HF-RFID canbe easily limited by restricting the size of the antenna on the tag. Incontrast, longer read-range RFID such as Ultra-high Frequency (UHF-RFID)may confusingly interrogate every RFID tag in the operating room andthus be unable to identify which medication is being delivered to themedication identification and measurement system 128, 228. However, anysuitable RFID range for a particular application may be used.

FIG. 3 illustrates a plan view of an example of preloaded syringes 306Aand 306B that can be used with the automated dose-response record system200 of FIG. 2.

The one or more preloaded syringes 306A and 306B may be labeled with aunique barcode label 307 or an RFID tag 308 that may identify one ormore of the drug, the concentration, the lot number, the expirationdate, the manufacturer and other important information. In someexamples, a unique barcode label 307 may be a “2-D” barcode label inorder to include more information on a smaller area than traditionalbarcode labels. In some examples, the barcode label 307 or RFID tag 308includes the drug identifying label 309A and 309B for convenient use bythe caregiver.

In some examples, the syringes 306A and 306B can be filled at the pointof use and may be labeled with drug labels 309A and 309B and eitherbarcode labels 307 or RFID tags 308 that are removably attached to thedrug bottle or vial at the factory or pharmacy. The drug labels 309A and309B and either barcode labels 307 or RFID tags 308 may be easilyremoved from the drug bottle or vial and adhesively attached to thesyringe 306A or 306B at the time that the syringe 306A or 306B is loadedwith the drug by the caregiver. Instead of, or in addition to thebarcode labels 307 or RFID tags 308, any other suitable “tag/reader”system known in the arts, may be used.

FIGS. 4-10 illustrate examples of medication identification andmeasurement systems 428, 628, 828 that can be used with the automateddose-response record systems 100, 200 of FIGS. 1 and 2. However, aspectsof the medication identification and measurement systems 428, 628 and828 may be used with other systems, and other medication identificationand measurement systems may be used with the automated dose-responserecord systems 100, 200. Furthermore, some examples of the automateddose-response record systems 100, 200 can omit aspects of the medicationidentification and measurement systems, or can omit a medicationidentification and measurement system altogether. FIG. 4 illustrates aportion of an automated dose-response record system 400 including a sideview of an example medication identification and measurement system 428and a syringe 406 that can be used with the automated dose-responserecord systems 100, 200 of FIGS. 1 and 2, to monitor drug delivery. FIG.5 illustrates a cross-sectional view of the medication identificationand measurement system 428 and the syringe 406 (not shown incross-section) of FIG. 4, taken along line 5-5. FIGS. 4 and 5 aredescribed together.

As shown FIGS. 4 and 5, the medication identification and measurementsystem 428 may include at least one injection portal 411 (also see 211,FIG. 2). The injection portal 411 may be a receptacle for accommodatinga syringe 406 in a fixed and known location and can be configured toorient the Luer taper connector 513 to mate with an injection port 515.The injection port 515 can be secured within the injection portal 411and can be in fluid communication with IV tubing 520. In some examples,the injection portal 411 may include an injection portal tube 416, suchas a transparent tube that is sized to receive and accommodate a syringebarrel 418 of a syringe 406. In some examples, the injection portal canbe configured to receive a specific size syringe barrel 418. In someexamples, multiple injection portals 411 can be provided to accommodatesyringes 406 of different sizes.

FIG. 6 illustrates a portion of an automated dose-response record system600 including a side view of a second example of a medicationidentification and measurement system 628 and a syringe 606 that can beused with the automated dose-response record systems 100, 200 of FIGS. 1and 2, to monitor drug delivery. FIG. 7 illustrates a cross-sectionalview of the second example of a medication identification andmeasurement system 628 and the syringe 606 (not shown in cross-section)of FIG. 6, taken along line 7-7. FIGS. 6 and 7 are described together.

As shown in FIGS. 6 and 7, the injection portal 611 of the medicationidentification and measurement system 628 may be large enough toaccommodate syringes 606 of multiple sizes within the space defined by areal or imaginary injection portal tube 616. In this example, accuratelyorienting the Luer taper connector 713 to mate with an injection port715 may be accomplished by one or more orienting members such as one ormore spring positioning members 622A-F that engage with the syringebarrel 618 to center it in the injection portal 611. In some examples,there may be two or more rows of spring positioning members 622A-F. Forexample, spring positioning members 622A, B, E, F may be located nearthe entrance to the injection portal 611 and spring positioning members622C, D may be located near the injection port 715 to assure accuratepositioning for mating with the Luer taper connector 713. Springpositioning members 622A-F may include not only spring wires or metal orpolymer or plastic spring pieces but any flexible material orcombination of materials or shapes that can be deformed by the syringebarrel 618 entering the injection portal 611 and retain a memory (e.g.,elastically deformable, substantially elastically deformable,resiliently deformable, resilient member) so as to urge the syringebarrel 618 into a centered position within the space defined by a realor imaginary injection portal tube 616.

One objective of the spring positioning members 622A-F can be to“automatically” center and align the Luer taper connector 713 of thesyringe 606 with the injection port 715, so that the operator can simplyand conveniently push the syringe 606 into the injection portal 611 andno further manual alignment may be needed. The spring positioningmembers 622A-F can also obviate the need for the operator to toucheither the Luer taper connector 713 of the syringe 606 or the injectionport 715, thus beneficially preventing accidental infectiouscontamination by the operators' fingers and gloves.

FIG. 8 illustrates a portion of an automated dose-response record system800 including a side view of a third example of a medicationidentification and measurement system 828 and a syringe 806 that can beused with the automated dose-response record systems 100, 200 of FIGS. 1and 2. FIG. 9 illustrates a cross-sectional view of the third example ofa the medication identification and measurement system 828 and thesyringe 806 (not shown in cross-section) of FIG. 8, taken along line9-9. FIGS. 8 and 9 are described together.

As shown in FIGS. 8 and 9, a syringe barrel 818 may be centered and heldin place by one or more orienting members, such as compressionpositioning members 842A,B. The compression positioning members 842A, Bmay be urged apart by inserting the syringe barrel 818 there between.Springs 844A-D can compress and create a pressure pushing thecompression positioning members 842A,B against syringe barrel 818. Thecompression positioning members 842A,B shown in FIGS. 8 and 9 are merelyillustrative, and many other sizes, shapes, numbers and locations ofcompression positioning members 842 are anticipated.

Compression positioning members 842A,B may be simple spring 844A-Dactivated devices (e.g., resilient members) as shown in FIGS. 8 and 9 ormay be any mechanism that can expand (e.g., resiliently expand) toaccommodate syringe barrels of various sizes and urge the syringe barrel818 into a centered position within the space defined by a real orimaginary injection portal tube 816. This example shows spring 844A-Dactivated compression positioning members 842A,B but many othermechanical activation mechanisms are anticipated. The compressionpositioning members 842A,B can be elastically deformable, substantiallyelastically deformable, resiliently deformable, include one or moreresilient members.

Other examples of positioning members designed to hold an insertedsyringe 806 in the center of the injection portal 811 and thus orientingthe Luer taper 913 for mating with the injection port 915 areanticipated. Positioning the inserted syringe 806 in the center of theinjection portal 811 allows the machine vision to work from a knowndistance and thus calculations of syringe plunger 948 movement can bevery accurate.

In some examples, instead of the positioning members shown in theexamples of FIGS. 6 — 9 holding a syringe centrally, the positioningmembers 622A- or 842A,B can be designed to hold an inserted syringe 606,806 at a known, but off center position in the injection portal 611,811, such as when the injection port 715, 915 (FIGS. 7 and 9) ispositioned off center in the injection portal 611, 811. Any arrangementof at least one positioning member that aligns an inserted syringe at aknown position may be provided.

In some examples, and as shown in FIGS. 4, 6 and 8 the medicationidentification and measurement system 428, 628, 828 of this disclosuremay include one or more “machine vision” cameras 436, 636, 836 thatinput digital images into one or more processors having processingcircuitry 157, 257 as shown and described in FIGS. 1,2, that isprogramed to analyze machine vision images. In some examples, one of theimages that the machine vision cameras 436, 636, 836 may “see” is abarcode label 307 on the syringe 406, 606, 806, that has been insertedinto the injection portal 411, 611, 811, for identifying the medicationin the syringe 406, 606, 806. As previously noted, the barcode label 307can identify the brand name and/or generic name of the medication in thesyringe. In some examples, the barcode label 307 also may identify oneor more of the concentration of the medication, the lot number, theexpiration date and other information that may be useful for inventorymanagement.

As shown in FIGS. 4, 6 and 8, the automated dose-response record system400, 600, 800 of this disclosure can include one or more radio frequencyidentification (RFID) interrogation antennas 438, 638, 838 that inputRFID information into a processor, such as processing circuitry 157, 257as shown and described in FIGS. 1 and 2, that is programed to analyzeRFID data. In some examples, the RFID interrogation antennas 438, 638,838 can interrogate a RFID tag 308 (FIG. 3) attached to the syringe 406,606, 806, that has been inserted into the injection portal 411, 611,811, for identifying the medication in the syringe 406, 606, 806. Insome examples, short range RFID such as near field (NF) or highfrequency (HF) may be advantageous because they may only detect thesyringe 406, 606, 806 that is adjacent to or inside the security systemfor IV medications 400, 600, 800, and not detect the various othermedication syringes that may be sitting on the worktable such as206A-206C in Fig.2.

As shown in FIGS. 4, 6 and 8 the medication identification andmeasurement system 428, 628, 828 of this disclosure may include a RFIDinterrogator 438, 638, 838. In some examples, the RFID interrogator 438,638, 838 that can include antennas that may be located inside themedication identification and measurement system 428, 628, 828 . In someexamples, the RFID interrogator antennas 438, 638, 838 may be locatedexternal to but proximate the medication identification and measurementsystem 428, 628, 828. As the syringe 406, 606, 806 is brought intoproximity of the medication identification and measurement system, theRFID interrogator 438, 638, 838 can interrogate the RFID tag 308 on thesyringe 406, 606, 806, thereby accurately and reliably identifying amedication for IV administration. In some examples, the RFID tag 308 orother marker may include one or more of: the generic and brand name ofthe drug, the concentration, the lot number, the expiration date, themanufacturer and other important information that may be recorded. Insome examples, the generic and brand name of the drug and theconcentration of the drug can be displayed in the injection section of adisplay such as the display 126, 226 (FIGS. 1, 2).

Machine vision is very accurate for measuring the size of an object at aknown distance or the distance of an object of known size. However, itcannot do both. Therefore, in some examples it is important to know theexact location of a syringe and thus know the distance from the camerato the syringe in order to accurately calculate the distance of themovement of the plunger within the syringe.

Syringes are available in multiple sizes such as 3cc, 6cc and 12cc, eachof which is a different diameter. The machine vision processor must knowboth the internal diameter of the barrel of the syringe and the distancethat the syringe plunger moves down the barrel, in order to calculatethe volume of medication injected, unless it has another source ofinformation. The machine vision of this disclosure can measure thediameter of the syringe because in the examples the syringe 406, 606,806 is held at known distance and in a centered location relative to themachine vision cameras 436, 636, 836. Alternately, the security systemfor IV medications 400, 600, 800 of this disclosure may be programed toknow that the particular hospital uses only Monoject® syringes forexample and the internal diameter of each Monoj ect® syringe size may bepre-programed into the computer. In this case, the machine vision onlyneeds to differentiate 3 cc, 6 cc and 12 cc syringe sizes from eachother. The machine vision processor can determine the internal diameterof the barrel of the syringe. In some examples, the syringe size may beincluded in the information provided by the barcode 307 or RFID 308(FIG. 3).

In some examples, such as the examples of FIGS. 4-9, the machine visionsystem, including the machine vision camera 436, 636, 836 and theprocessor 157, 257 of FIGS. 1 and 2 (e.g., processing circuitry) inelectrical communication with the machine vision camera 436, 636, 836,can visually detect and determine other geometry information about thesyringe 406, 606, 806 besides the outside diameter, such as determiningthe inside diameter, or the inner or outer length of the syringe. Themedication identification and measurement systems 428, 628, 828 can usethe geometry information to determine the size or type of the syringe406, 606, 806, or can use the geometry information to calculate a volumeof the syringe 406, 606, 806.

In some examples, as the syringe 406, 606, 806 is advanced into theinjection portal 411, 611, 811, the image of the syringe 406, 606, 806entering the injection portal 411, 611, 811 is displayed in real time inan injection section 126a, 226a of the display 126, 226 (FIGS. 1 and 2).Therefore, the caregiver can watch the syringe 406, 606, 806 advance andengage with the injection port 515, 715, 915. In some examples, theinjection portal tube 416, 616, 816 or the spring positioning members622A-E or the compression positioning members 842A,B, urge the syringe606, 806 into position to mate with the injection port 715, 915 but theactual connection can also be observed as it is happening by thecaregiver on the display 126, 226. Even though the caregiver is notphysically holding the injection port 515, 715, 915 as they typicallywould, they can watch the engagement of the Luer connector 513, 713, 913with the injection port 515, 715, 915 on a display 126, 226, the view isessentially identical to the thousands of injections that they have madeduring their career. In some examples, the actual image of the syringe406, 606, 806 can be displayed on the display 126, 226, while in otherexamples the data obtained by the camera 436, 636, 836 can be convertedto a representation of the syringe displayed on the display 126, 226.

In some examples, once the syringe 406, 606, 806 is securely connectedto the injection port 515, 715, 915, the caregiver pushes on the plunger446, 646, 846 of the syringe 406, 606, 806, injecting the medicationinto the injection port 515, 715, 915 and IV tubing 520, 720, 920. Thecaregiver can visualize the plunger seal 548, 748, 948 move down thesyringe barrel 418, 618, 818 and can determine the volume of medicationinjected by the graduated markings on the syringe 406, 606, 806. Thus,the engagement of the Luer connector 513, 713, 913 with the injectionport 515, 715, 915 and the injected volume are observed by the caregiveron the display 126, 226 and the traditional method and routine ofinjection is minimally altered by implementing the automateddose-response record system 100, 200 including the example medicationidentification and measurement systems 428, 628, 828.

In some examples, the processing circuitry 157, 257 (FIGS. 1 and 2) or acomputer may also simultaneously generate data representing a runningtotal of the volume and dosage of the injected medication and cantransmit the generated data to the display 126, 226 to display volumeand dosage information on the display 126, 226. In some examples, theprocessing circuitry 157, 257 or a computer may also generate its owngraduated scale and transmit the generated graduated scale informationto the display 126, 226 to superimpose the scale on the image of thesyringe 406, 606, 806 or next to the image of the syringe 406, 606, 806,for added visual clarity of the injected volume and dose.

In some examples, the machine vision determination of the injectedvolume may be calculated by multiplying the internal cross-sectionalarea of the syringe (πr²) by the distance that the syringe plungermoves. The radius of the syringe may be determined in one or more ways.For example, the machine vision function may determine that the syringeapproximates a 3 cc or 12 cc syringe and the computer is programed toknow that the hospital uses a specific brand of syringes and theinternal diameter (radius) of each of these syringe sizes is preciselyknown. (An example of diameter D, radius R, longitudinal direction, axisor centerline C is shown in FIG. 5) Another example may require themachine vision camera to measure the outer diameter of the syringe andthen subtract an approximated wall thickness (either measured or knownvalue stored in a memory) from the measured diameter to determine theinternal diameter. In another example, the internal diameter of thesyringe may be supplied to the processing circuitry 157, 257 or acomputer as part of the RFID 308 or barcode 307 information. In anotherexample, the machine vision may determine the inner diameter of thesyringe by determining an outer diameter of the plunger as viewedthrough the transparent or semi-transparent syringe and determine thewall thickness, In yet another example, the machine vision may be ableto visibly determine the inner diameter or radius directly through thetransparent or semi-transparent syringe. Any other suitabledetermination, calculation or algorithm may be used to determine theradius, diameter and injected volume.

In some examples, the machine vision determination of the distance thatthe syringe plunger 446, 646, 846 moves may be by “observing” themovement of the black rubber plunger seal 548, 748, 948 against thevisible scale printed on the syringe 406, 606, 806. In this example, themachine vision can be programed to recognize the markings on the syringe406, 606, 806.

In some examples, the machine vision determination of the distance thatthe syringe plunger 446, 646, 846 moves may be by observing the movementof the black rubber plunger seal 548, 748, 948 relative to a scalecalculated by the processing circuitry 157, 257 (FIGS. 1 and 2). Thegeometrical calculation of the scale that determines the distance thatthe syringe plunger 446, 646, 846 moves may be easiest to determinealong the widest part of the syringe that corresponds with the center C(FIG. 5) of the syringe 406, 606, 806, which is a known distance fromthe machine vision camera 436, 636, 836. Alternatively, thecomputer-constructed scale may be applied to the side of the syringe406, 606, 806 facing the camera 436, 636, 836, if the radius of thesyringe 406, 606, 806 is subtracted from the known distance to thecenter C (FIG. 5) of the syringe 406, 606, 806 in order to calculate thedistance 437 from the machine vision camera 436, 636, 836 to the nearside (e.g., 411A) of the syringe 406, 606, 806.

In some examples, the movement of the black rubber plunger seal 548,748, 948 of the syringe 406, 606, 806 can be clearly identifiable by themachine vision camera 436, 636, 836 and a scale to determine thedistance moved by the plunger 446, 646, 846 can either be “visualized”or constructed by the machine vision computer (e.g., processingcircuitry). Multiplying the distance that the plunger seal 548, 748, 948moves by the known or measured internal diameter d (FIG. 5) of thesyringe 406, 606, 806 and thus cross-sectional area of the plunger seal548, 748, 948, allows the processing circuitry 157, 257 or a computer inelectrical communication with the processing circuitry 157, 257 tocalculate an accurate injected volume. The measured injection volume anddosage may be displayed on the display 126, 226 of the module 101, 201(FIGS. 1 and 2). Without interfering with or changing theanesthesiologists' normal or traditional medication injection routines,an unobtrusive machine vision camera 436, 636, 836 and computer (e.g.,processing circuitry) can “observe” the medication injections andautomatically record them in the EMR.

In some examples, the injected volume of medication may be determined byother sensors or methods. For example, the systems described herein canemploy (e.g., substitute) other sensors such as a non-visual opticalsensor 436A in place of or in addition to the machine vision camera 436,636, 638 described in FIGS. 4-9. For example, a light source can shineon one or more light sensitive elements such as photodiodes, and theposition of the plunger of the syringe can be roughly determined by theobstruction of the light beam by the plunger. Other fluid measurementmethods can have a sensor including adding magnetic material to thesyringe plunger and detecting movement of the plunger with a magneticproximity sensor. Alternatively, fluid flow may be measured with fluidflow meters in the IV fluid stream. These examples are not meant to bean exhaustive list but rather to illustrate that there are alternativetechnologies to machine vision (e.g., sensors), for noncontactmeasurement (e.g., sensing) of fluid flow from a syringe that areanticipated in this disclosure.

In some examples, the injected volume of medication may be determined byother sensors or methods. For example, the systems described herein canemploy (e.g., substitute) other sensors in place of or in addition tothe machine vision cameras for either or both the medication and fluidflows. Other fluid flow sensors anticipated by this disclosure includebut are not limited to: ultrasonic flow meters, propeller flow meters,magnetic flow meters, turbine flow meters, differential pressure flowmeters, piston flow meters, helical flow meters, vortex flow meters,vane flow meters, paddle wheel flow meters, thermal flow meters,semicylindrical capacitive sensor flow meters and Coriolis flow meters.

Securing the injection port 515, 715, 915 within the injection portal411, 611, 811 prevents the caregiver from touching the injection port515, 715, 915. Normally caregivers wear gloves to protect themselvesfrom infectious contaminates from the patient and operating room andtheir gloves are nearly always contaminated. Anything they touch will becontaminated. They typically pick up and hold the IV injection port 515,715, 915 with one hand while inserting the Luer taper connector 513,713, 913 of the syringe 406, 606, 806 into the injection port 515, 715,915. In the process, the injection port 515, 715, 915 is frequentlycontaminated with pathogenic organisms from their gloves that can enterthe patient's blood stream with the next injection, causing seriousinfections. It is therefore advantageous from the infection preventionpoint of view, if the Luer connection and injection can be accomplishedwhile never touching the injection port 515, 715, 915.

In some examples as shown in FIGS. 4, 6 and 8 the medicationidentification and measurement system 428, 628, 828 can include one ormore ultraviolet (UV) lights 440A, 440B, 640A-D, 840A-D that shine onthe injection port 515, 715, 915. The one or more UV lights can belocated inside the module (e.g., 101, FIG. 1) of the medicationidentification and measurement system 128, 228, 428, 628, 828, keepingthe injection portal 411, 611, 811 and the injection port 515, 715, 915disinfected. In some examples, the UV lights 440A, 440B, 640A-D, 840A-Dmay preferably be in the UV-C part of the light spectrum. UV-C light hasbeen shown to have superior germicidal powers over other parts of the UVspectrum. The UV lights 440A, 440B, 640A-D, 840A-D may shinecontinuously or intermittently. By making the injection port 515, 715,915 untouchable because it is inside the module 101 and radiating theinjection port 515, 715, 915 with UV-C light, the injection port 515,715, 915 should be effectively disinfected between each injection andthereby eliminate injection port 515, 715, 915 contamination as a sourceof bloodstream infection.

In some examples as shown in FIGS. 1 and 2, the automated dose-responserecord system 100, 200 may include an external reader, such as barcodereader 180, 280 on the module 101, 201 to read a barcode, QR code or thelike for identification. This barcode reader 180, 280 may be used toidentify the healthcare provider injecting a medication by reading abarcode or QR code 1186 on the user's ID badge for example (FIG. 11). Insome examples as shown in FIGS. 1 and 2, the automated dose-responserecord system 100, 200 may include an external RFID reader 182, 282 onthe module 101, 201. This RFID reader 182, 282 may be used to identifythe healthcare provider injecting a medication by reading an RFID tag1188 on the user's ID badge 1184B for example (FIG. 11). In someexamples as shown in FIGS. 4, 6 and 8, the automated dose-responserecord system 400, 600, 800 may include an internal RFID reader 438,638, 838 in the module 101, 201. This RFID reader 438, 638, 838 may alsobe used to identify the healthcare provider injecting a medication byreading an RFID tag on the user's ID badge for example.

It is an important part of the record to know who injected themedication and their identity can be easily verified and documented bythe automated dose-response record system 400, 600, 800 using eitherbarcode, QR code or RFID. Other identification technologies are alsoanticipated.

FIG. 10 illustrates an example injection port cassette 1054 that can beused with the automated dose-response record systems 100, 200 of FIGS. 1and 2, as detailed in FIGS. 5, 7 and 9. As shown in FIG. 10, theinjection port 1015 may be mounted on an injection port cassette 1054 inorder to make the attachment to the automated dose-response recordsystem 100, 200, 400, 600, 800 easier and more secure. The injectionport cassette 1054 may be a piece of molded polymer or plastic ontowhich the injection port 1015 and IV tubing 1020 may be attached. Theinjection port cassette 1054 may be shaped and sized to fit into a slotin the automated dose-response record system 100, 200, 400, 600, 800.When the injection port cassette 1054 is fit into a slot in theautomated dose-response record system 100, 200, 400, 600, 800, theinjection port 1015 can be positioned substantially in the center of theinjection portal 411, 611, 811 for mating with the Luer tapers 513, 713,913. The injection port cassette 1054 can also be configured to beremoved intact from the automated dose-response record system 400, 600,800 so that the patient can be transferred and the IV tubing 1020 can bemoved with the patient and continue to operate normally.

In some examples, and as shown in FIG. 10, the injection port cassette1054 can include an IV bypass channel 1056 in the IV tubing 1020. The IVbypass channel 1056 can allow the IV fluids to flow unencumbered by themedication injection apparatus. The injection port cassette 1054 caninclude a medication channel 1058 in the IV tubing 1020 and, themedication channel 1058 may include one or more stop-flow clamps1060A,B. The one or more stop-flow clamps 1060A,B may be activated bythe automated dose-response record system 100, 200, 400, 600, 800 if amedication error is identified. The one or more stop-flow clamps 1060A,Bmay be powered by one or more electromechanical solenoids that squeezethe IV tubing in the medication channel 1058 flat, obstructing the flow.Other electromechanical flow obstructers are anticipated.

In some situations, such as when administering a drug to a patientallergic to that drug, or administering potent cardiovascular drugs to apatient with normal vital signs, or administering a drug with a likelymistaken identity, the computer, such as processing circuitry 157, 257(FIGS. 1 and 2) for the automated dose-response record system 100, 200,400, 600, 800 of this disclosure can automatically activate thestop-flow clamps 1060A,B to compress the medication channel 1058 tubingupstream and/or downstream from the injection port 1015. Compressing theIV tubing both upstream and downstream from the injection port 1015prevents the injection of any medication into the IV tubing 1020. Analert to the adverse condition of the injection may be displayed ondisplay 126, 226 where the stop-flow condition can be over-ridden by theoperator touching a manual override switch on the display 126, 226 orthe module 101, 201, if the injection was not erroneous. While thestop-flow can occur in the medication channel 1058, the IV fluid flowcan continue normally in the parallel bypass channel 1056.

The stop-flow clamps 1060A,B can allow the processing circuitry 157, 257(e.g., processor, hardware processing circuitry) of the automateddose-response record system 100, 200, 400, 600, 800 to not only warn theoperator of a pending medication error, but physically prevent theinjection. Perhaps equally as important is that the stop-flow clamps1060A,B can be quickly released by the operator touching a manualoverride switch in the event that the apparent error was in fact aplanned event or otherwise desired by the operator.

In some examples, a part of the automated dose-response record system100, 200, 400, 600, 800 can include the ability for the computer (e.g.,machine) to know the patient's medical history, medication orders, vitalsigns, current medications, medication orders and other importantinformation about that patient. In some examples, the medication insyringe 306 can be identified by RFID tag 308 (FIG. 3) and is detectedby RFID interrogator 438, 638, 838 as the syringe 306 enters injectionportal 411, 611, 811. The processing circuitry (e.g., 157, 257) of theautomated dose-response record system 100, 200, 400, 600, 800 cancross-reference the proposed injection to the patient's medical history,medication orders, vital signs, current medications and other importantinformation about that patient, providing a safety “over-watch” guardingagainst medication errors. In some examples, the processing circuitry(e.g., 157, 257) of the automated dose-response record system 100, 200,400, 600, 800 may include algorithms and/or “artificial intelligence”that can provide alternative medication suggestions based on patient'smedical history, medication orders, vital signs, current medications andother important information about that patient.

In some examples, the EMRs that are created by the automateddose-response record system 100, 200, 400, 600, 800 of this disclosurecan provide accurate and temporally correlated information about therelationship between any injected medication and the resultingphysiologic response. This is uniquely accurate dose-response data notavailable in current processes or systems. In some examples, the EMRsthat are created by the automated dose-response record system 100, 200,400, 600, 800 for hundreds of thousands or even millions of patients,may be aggregated and analyzed as “big data.” The “big data” from theseEMRs may be used for a variety of purposes including but not limited tomedical research, patient and hospital management and the development of“artificial intelligence” algorithms that can provide alternativemedication suggestions. Ongoing “big data” from more and more EMRs canbe used to continually improve and refine the “artificial intelligence”algorithms. These “artificial intelligence” algorithms can be used toprovide automated (“self-driving” or “partially self-driving”)anesthesia during surgery or automated medication delivery.

FIG. 11 illustrates a plan view of an example of healthcare provider IDbadges 1184A and 1184B that can be used with the system of FIGS. 1 and2, in accordance with at least one example. In some examples, the “chainof custody” may begin by electronically identifying the healthcareprovider as the drugs are checked out from the pharmacy or Pixismedication dispenser. In some examples and as shown in FIG. 11, eachprovider can have a personalized RFID tag 1186, attached to theirhospital ID badge 1184A. In some examples each provider can have apersonalized barcode 1188, attached to their hospital ID badge 1184B forexample. When the drugs are checked out, the personalized RFID tag 1186may be read by an RFID interrogator or the personalized barcode 1188read by a barcode reader in the pharmacy and the ID of the providerchecking the drugs out may be noted in the hospital's computer and/orthe processing circuitry 157, 257 (FIGS. 1 and 2) for the automateddose-response record system 100, 200, 400, 600, 800 (FIGS. 1, 2, 4, 6and 8). The specific RFID 308 or barcode 307 (FIG. 3) identification ofthe injectable drug may also be recorded before the drug leaves thepharmacy and that information may be transmitted to the processingcircuitry 157, 257 of the automated dose-response record system 100,200, 400, 600, 800 of this disclosure. In some examples, instead of anRFID tag 1186 and RFID reader, other provider identification informationand sensors for identifying the provider can be used, such provideridentification information may include: a barcode, a QR code with thesensor being able to read such codes. In other examples, the sensor caninclude a retinal scanner, fingerprint reader or a facial recognitionscanner that identifies the provider by personably identifiableinformation (e.g., provider identification information) may be used.

In some examples, when the provider arrives at the patient's bedside,the provider may be identified by their ID badge 1184 A,B. In someexamples, an ID badge 1184A that has an RFID tag 1186 may be read byRFID reader 182, 282 (FIGS. 1 and 2) that can be located on theautomated dose-response record system 100, 200, 400, 600, 800 or by RFIDreader 438, 638, 838 (FIGS. 4, 6 and 8) located inside the automateddose-response record system 100, 200, 400, 600, 800 (FIGS. 1, 2, 4, 6and 8). In some examples, an ID badge 1184B that has a barcode 1188 maybe read by barcode reader 180, 280 that can be located on the automateddose-response record system 100, 200, 400, 600, 800. In some examples, aretinal scanner may be located on or near module 101, 201 in order topositively identify the provider by their retinal vasculature. Otherscanners including but not limited to facial recognition scanning arealso anticipated in order to positively identify the provider doing theinjection in order to automatically document this information to an EMRor other record.

In some examples, the provider's photograph may be taken by camera 190,290 (FIGS. 1 and 2) for further identification before allowing theinjection of scheduled drugs. In some examples, the camera 190, 290 maybe triggered, such as by processor 157, 257 (FIGS. 1 and 2), when asyringe e.g., 306B filled with a scheduled drug such as a narcotic isidentified as it enters the injection portal 411, 611, 811 and the RFIDinterrogator 438, 638, 838 interrogates the RFID tag 308 (FIG. 3) or themachine vision camera 436, 636, 836 reads the barcode 307 (FIG. 3) onthe syringe 306A. Non-scheduled medications may not need the addedsecurity of a photograph.

In some examples as shown in FIGS. 1 and 2, the automated dose-responserecord system 100, 200 of this disclosure may include a remote monitorwith display 187, 287. The remote monitor may include a wired orwireless connection to the automated dose-response record system 100,200 and may display some or all of the information shown on theelectronic record display 126, 226, or other information generated bythe automated dose-response record system 100. For example, theprocessing circuitry 157, 257 can be in electrical communication withthe remote display 187, 287 and the processing circuitry 157, 257 cansend instructions to the remote display 187, 287 to display thegenerated information.

The remote monitor may be in the next room or miles away. The remotemonitor may allow remote supervision of healthcare delivery. Forexample, anesthesiologists frequently supervise up to four surgicalanesthetics at once, each being delivered by a nurse anesthetist. Inthis case, the anesthesiologist carrying a wireless remote monitor 187,287 can have real-time data on each case under their supervision.Similarly, a nurse anesthetist working in a rural hospital may besupervised by an anesthesiologist who is 50 miles away.

In some examples, the remote monitor with display 187, 287 can create arecord for billing. For example, when an anesthesiologist is supervisingmultiple anesthetics at once, the payers may dispute the involvement ineach case and refuse to pay. The remote monitor with display 187, 287may include an RFID reader that documents the close proximity of an RFIDtag on the anesthesiologist's ID badge. Any other type of proximitysensor may be used in place of the RFID tag, including but not limitedto GPS location sensing. Documenting that the anesthesiologist wascarrying the remote monitor with display 187, 287 throughout the time ofthe surgery is very good evidence that the anesthesiologist was activelyparticipating in the care of the patient.

In some examples, the remote monitor with display 187, 287 allowslong-distance medical consultation. For example, an expert at the MayoClinic could consult with a physician halfway around the world in Dubai,responding to real-time patient data displayed on the remote monitorwith display 187, 287.

FIG. 14 illustrates a side view of an example IV fluid identificationand measurement system 1430 that can be used with the systems of FIG.1-9, and the injection port cassette of FIG. 10. Some aspects of FIGS.1-14 are described together, however, the examples are merelyillustrative and the features can be used in any suitable combination.In some examples, the automated dose-response record system 100, 200 ofthis disclosure includes a system for automatically measuring andrecording the administration of IV fluids. To accomplish this, as shownin FIGS. 1, 2 and 14, the automated dose-response record system 100, 200can include an IV fluid identification and measurement system 130, 230,1430. In some examples, the IV fluid identification and measurementsystem 130, 230, 1430 can be mounted onto module 101.

Alternately, the IV fluid identification and measurement system 130,230, 1430 may be mounted to an IV pole 105 or racking system independentfrom the module 101. The system for automatically measuring andrecording the administration of IV fluids is not limited to use inanesthesia or in the operating room, but has applicability for usethroughout the hospital and other health care settings, including butnot limited to the ICU, ER, wards, rehabilitation centers and long termcare settings. In some examples, aspects of the IV fluid identificationmeasurement system 130, 230, 1430 can be provided alone or together withother features of the automated dose-response record system 100, 200including the medication identification and measurement system 128, 228.

In some examples, the IV fluid identification and measurement system130, 230, 1430 may be configured to accommodate one or more bags of IVfluid 132, 232A,B and 1432A,B. Each bag of IV fluid can include a dripchamber 134, 234A,B and 1434A,B and IV tubing 120, 220A,B and 1420A,B.IV flow rates may be controlled with the traditional manually operatedroller clamp that variably pinches the IV tubing 120, 220A,B and 1420A,Bto control or even stop the flow of IV fluids. In some examples, IV flowrates may be controlled with the automatically operatedelectromechanical flow rate clamps 1478 that variably pinch the IVtubing 1420A to control or even stop the flow of IV fluids. Theautomatically operated electromechanical flow rate clamps 1478 may becontrolled by the processing circuitry 157, 257, such as an electronicanesthetic record computer in module 101 or by any other suitableprocessor including hardware processing circuitry that is in electricalcommunication with the IV fluid identification and measurement system130, 230, 1430 and/or is located within the IV fluid identification andmeasurement system 130, 230, 1430.

In some examples, the IV fluid identification and measurement system130, 230, 1430 is configured to automatically measure and record theadministration of IV medications and fluids. The system 130, 230 caninclude one or more of a barcode reader and an RFID interrogator (suchas 1436A,B) for accurately and automatically identifying a fluid for IVadministration. Because of the close proximity to the adjacent bags,barcode identification may be preferable in order to prevent an RFIDinterrogator from reading the RFID tag on a neighboring bag. In someexamples, as shown in FIG. 14, one or more barcode labels 1405A,B may beapplied to the IV bags 1432A,B in a location where they can be read by asensor such as a barcode reader or machine vision camera 1436A,B, oranother machine vision camera located in a suitable position to read thebarcode. In some examples, a dedicated barcode reader or a machinevision camera may be positioned adjacent the barcode label 1405A,Blocation, specifically for reading the barcode label 1405A,B.

In some examples, the drip chamber 234A,B and 1434A,B of the IV set canbe positioned adjacent the one or more machine vision cameras 1436A,B.In some examples, a standard background 1468A,B may be positioned on theopposite side of the drip chamber 1434A,B from the machine visioncameras 1436A,B. The standard background 1468A,B may be a plainbackground or may be an advantageous color, pattern, color design orillumination that highlights each of the falling drops, for easieridentification by the processing circuitry 157, 257 (e.g., 1502, FIG.15). The machine vision software including instructions can be stored onone or more machine-readable mediums (such as 1522 in FIG. 15) that whenimplemented on hardware processing circuitry (including but not limitedto processing circuitry 157, 257) or in electrical communication withthe system, can perform the functions described herein. An example ofsuch electrical connection is shown by the connection of processor 1502with mass storage 1516 in FIG. 15.

In some examples, the processing circuitry 157, 257, 1502 can beconfigured to look for (e.g., sense, monitor, detect) a fluid meniscus1464A,B in the drip chamber 1434A,B. In this case “seeing” a fluidmeniscus 1464A,B indicates that there is fluid in the drip chamber1434A,B and therefore the IV bag 1432A,B is not empty, and air is notinadvertently entering the IV tubing 1420A, 1420B.

In some examples, if the IV fluid identification and measurement system130, 230, 1430 fails to “see” a fluid meniscus 1464A,B meaning that thedrip chamber 1434A,B is empty and thus the IV bag 1432A,B is empty,stop-flow clamps 1460A,B can be automatically activated. For example,processing circuitry 157, 257 can send an instruction to activate thestop-flow clamps 1460A,B to compress the IV tubing 1420A,B in order toprevent air from entering the IV tubing 1420A,B. In some examples, theempty IV bag 1432A,B condition detected by the processing circuitry 157,257 can cause an alert to be displayed to the caregiver on theanesthetic record display 226, such as by sending an instruction to thedisplay.

The combination of the machine vision camera 1436A,B in electricalcommunication with processing circuitry (e.g., 157, 257, FIGS. 1 and 2)that executes instructions stored on a machine readable medium can countthe number of drops of fluid per unit of time in a drip chamber 1434A,Bto calculate or to estimate the flow rate of an IV. The size of the dripchamber 1434A,B inlet orifice determines the volume of liquid in eachdrop. The inlet orifices of standard drip chambers are sized to createdrops sizes that result in 10, 12, 15, 20, 45 and 60 drops per ml. Givena particular drop volume (size), 10 drops per ml for example, the system130, 230, 1430 (e.g., via sensors, processing circuitry and machinereadable medium) can count the number of drops falling in a known periodof time and use that data to calculate or to estimate the flow rate. Ifthese estimates were attempted by a human, they may be less accurate athigher flow rates (higher drop counts) because the drops are so fast, itcan be difficult to count the drops. Eventually, at even higher flowrates the individual drops become a solid stream of fluid and the flowrate cannot be visually estimated.

In some examples, the IV fluid identification and measurement system130, 230, 1430 is configured to look for falling drops of fluid 1462A,Bwithin the drip chamber 1434A,B. When drops 1462A,B have beenidentified, the machine vision system (e.g., machine vision camera 1436Aor 1436B operably coupled to processing circuitry 157, 257) may firstmeasure the diameter of the drop 1462A,B to determine which of thestandard drop sizes or volumes it is counting. Most hospitalsstandardize on several infusion set sizes, 10, 20 and 60 drops per ccfor example. Therefore, when these limited choices of infusion setbrands and sizes have been programed into the computer, the machinevision system only needs to differentiate between these choices, whichis much easier than accurately measuring the diameter of the drops.Unlike the human eye, the machine vision can accurately count thefalling drops even at high flow rates to calculate an IV fluid flowrate.

In some examples, the machine vision system, including the machinevision cameras 1436A,B and instructions 1524 (e.g., software) stored ona machine readable medium 1522 and implemented by hardware processingcircuitry 157, 257 does not “see” falling drops 1462A,B. In thissituation, either the fluid is flowing in a steady stream that is notidentifiable or the fluid has stopped flowing. In some examples, thesetwo opposite conditions can be differentiated by inserting a floatingobject 1466A,B (hereinafter, “float”) into the drip chambers 1434A,B. Insome examples, the float 1466A,B may be a ball-shaped float 1466A,B. Insome examples, the float may be patterned or multi-colored to moreeasily identify movement or spinning of the float. In some examples, ifthe machine vision system cannot identify falling drops 1462A,B, it thenlooks to the float 1466A,B for additional information. If the float1466A,B is not moving or spinning, the fluid flow has stopped. If thefloat 1466A,B is moving or spinning and drops cannot be identified, thefluid is flowing in a steady stream and the flow rate cannot be measuredby machine vision. In this situation, the system can determine fluidflow using an alternate method.

In some examples, the IV fluid identification and measurement system130, 230, 1430 may be configured to accommodate one or more bags of IVfluid 132, 232A,B, 1432A,B and each of these IV bags may be hanging froman electronic IV scale 1472A,B (e.g., a weight, a physicalcharacteristic sensor). The electronic IV scale 1472A can measure thecombined weight of the IV bag and fluid 1432A, the drip chamber 1434Aand the IV tubing 1420A. The electronic IV scale 1472B can measure theweight or combined weight of one or more of the IV bag and fluid 1432B,the drip chamber 1434B, the IV tubing 1420B and a pressure infuser 1474.In both of these examples, the electronic IV scale 1472A,B canaccurately measure the change in combined weight that occurs due to thedrainage of the IV fluid from the IV bag 1432A,B. The change in weightper unit time can be converted to flow rates by processing circuitry157, 257 in electrical communication with the electronic IV scale 1472A,1472B, for example, by the processing circuitry 157, 257, 1502 anddisplayed on the electronic record display 126, 226.

In some examples, the calculated flow rates for each IV bag 1432A,B mayalso be displayed on one or more digital flow-rate displays 1476A,Bmounted on the IV fluid identification and measurement system 1430. Thedigital flow-rate displays 1476A,B may be small LED or LCD displays thatconveniently tell the operator the flow rate while they are manuallyadjusting the flow rate near the IV bags 1432A,B and drip chambers1434A,B. The digital flow-rate displays 1476A,B are particularlyconvenient when the IV fluid identification and measurement system 130,1430 is a free-standing entity mounted on an IV pole 105 for examplewhile being used on the ward or ICU.

In some examples, when the falling drops 1462A,B cannot be detected andyet the floats 1466A,B are moving or spinning, the fluid is determinedto be flowing in a steady stream and the flow rate cannot be measured bymachine vision. In this case the electronic record computer mayautomatically query the change in weight per unit time as measured bythe electronic IV scale 1472A,B to determine the IV flow rate. At highflow rates, the change in weight per unit time as measured by theelectronic IV scale 1472A, B will most likely be more accurate thancounting drops, in determining the IV flow rate.

The IV flow rate as determined by the change in weight per unit time canalso be compared to the IV flow rates determined by counting drops toverify the accuracy of each method. Without interfering with or changingthe healthcare providers normal or traditional IV routines, anunobtrusive machine vision camera and computer can “observe” the IV flowrates and automatically record them in the EMR.

The module or automated EMR system 101, 201 of this disclosure maycapture anesthetic event data but it must be noted that the sametechnologies described herein for capturing anesthetic event data can beused throughout the hospital or outpatient health care system to captureand record medication administration, IV fluid administration, vitalsigns and patient monitor inputs, provider events and other data.Non-operating room heath care locations are included within the scope ofthis disclosure. While this disclosure focuses on the totality offunctions offered by module 101, 201, each of the individual functionscan be offered independently of module 101, 201.

The use of the term Electronic Anesthetic Record (EAR) as defined hereincan include any memory such as an electronic surgical record (ESR), oran electronic medical record (EMR), and is not limited to anesthetic orsurgical applications. Aspects of the modules 101,201 described hereincan also be employed in recovery, hospital room and long-term caresettings.

In an example, the module 201 of FIG. 2, can include a housing 299having a lower section 299A and a tower-like upper section 299B, whereinthe lower section 299A can be configured to house unrelated wasteheat-producing electronic and electromechanical surgical equipment, andwherein the tower-like upper section 299B can be located on top of thelower section 299A. The module 201 can also include a cowling 299Cexternal or internal to the housing 299 that substantially confineswaste heat generated by the unrelated waste heat-producing electronicand electromechanical surgical equipment. In addition, the module 201can include a system for monitoring the administration of one or more IVmedications and fluids 228, 230. As shown in the combination of FIGS. 2,4, 5 and 14, the system 228, 230 can include any of: a barcode 436reader or an RFID 438 interrogator configured to identify the one ormore IV medications or fluids; a machine vision digital camera 436 tocapture an image of one or more of a syringe 406 or a drip chamber1434A,B; processing circuitry 257 operably coupled to the barcode reader436 or the RFID interrogator 438 (or the machine vision digital camera436) to receive the identity of the one or more IV medications orfluids, the processing circuitry 257 operably coupled to the machinevision digital camera 436 to receive the captured image and determine avolume of medication administered from the syringe or fluid administeredfrom an IV bag based on the image; and a display 226 operably coupled tothe processing circuitry 257, the display 226 configured to receiveinstructions from the processing circuitry 257 to output the identityand determined volume of medication administered from the syringe orfluid administered from an IV bag.

“Dose-response” can be a useful medical process. Dose-response includesgiving something to the patient (a medicine for example) or doingsomething to the patient (mechanical ventilation or surgery forexample)—the “dose”, and then observing the patient's “response.”

Healthcare data in general is not automated. Healthcare data in generalis also not granular (e.g., beat-by-beat, second-by-second, continuous)but rather very intermittent (e.g., every 15 minutes, every 4 hours,every day etc.). In general, most data in the EMR are simply data thatwas on the old paper record, manually entered into the EMR. There areknown conventional systems including healthcare “dose events” that areautomatically digitized and automatically entered into the EMR or otherdatabases.

Manual data entry of dose events, whether they are reporting medicationinjections, fluid infusions or changes in the ventilator settings or anyother “dose events” are laborious, distracting and universally dislikedby healthcare providers. Perhaps more important is that the dose eventsare not accurately recorded. First, there are innocent errors inrecording. Second, there are omissions that may be innocent or for lackof time or due to provider sloppiness. Finally, there is no temporalcorrelation between a dose event and a related response event becausethe dose event is most likely manually recorded minutes to hours afterthe dose event occurred (if it is recorded at all).

At this date, even response data generated by physiologic monitors isnot recorded beat-by-beat, but rather intermittently recorded every 30minutes or 4 hours for example—just as it was historically recorded onthe paper record. The remainder of the response data must be manuallyentered into the record and thus suffers from the same limitations asnoted above for the manually entered dose events. As a result, withcurrent EMRs the dose and response data cannot be temporally correlatedwith any accuracy, vastly reducing the analytical and predictive valueof the electronic database and record. The systems described hereinprovide a technical solution to a technical problem. Furthermore, thebenefits achieved by the technical solutions of this disclosure exceedwhat can be accomplished by manual processes.

In some examples, the automated dose-response record system 100,200 ofthis disclosure includes systems and methods for constructing granular(beat-by-beat, second-by-second) anesthetic, surgical and patientrecords that include both “dose” events—the things that are given ordone to the patient (inputs from medication injection and fluidmonitors, various support equipment and machine vision “observations”for example) and “response” events (inputs from electronic physiologicmonitors, various measurement devices and machine vision “observations”for example). In some examples, the automated dose-response recordsystem 100,200 of this disclosure automatically enters both dose andresponse events into the electronic record. In some examples, the doseand response events of this disclosure are continually recorded,creating a much more granular record than is possible in conventionalelectronic records.

In some examples, the automated dose-response record system 100,200 ofthis disclosure automatically enters both dose and response events intothe electronic record and temporally correlates the dose and responseevents when they are recorded. Temporally correlating the dose andresponse data can be accomplished by recording dose and response data inparallel, adding integrated or external time stamps to the dose andresponse data or any other suitable method of temporally matching thedata sets.

In some examples, the automatically entered, temporally correlated doseand response events in the patient's electronic medical record (EMR) maybe analyzed by artificial intelligence (AI) and/or machine learning (ML)software in the processing circuitry of the module for immediateadvisory, alerts and feedback to the clinician. The patient's own datacan be analyzed by AI algorithms that were derived from general medicalknowledge and research or may be analyzed by AI algorithms that werederived from AI analysis of the pooled database of many patients, suchas machine learning (ML), traditional mathematical analysis or acombination thereof.

In some examples, the automatically entered, temporally correlated doseand response events in the patient's electronic record may be pooledwith the records of other patients in a database that can be analyzedwith artificial intelligence and machine learning software stored on amemory and executed by processing circuitry. This analysis can occur atthe time of temporal correlation or at a later time. This type ofanalysis is sometimes known as “big data.” The pooled data (e.g.aggregated data, compiled data, such as collective data of a group ofpatients, collective data for a specific patient over different periodsof time, doses, responses, medications, providers) may be stored onproprietary servers or may be stored in “the cloud.” In any event, the“big data” database of this disclosure is complete and granular(compared to current healthcare databases) because it was automaticallyentered and at least some of the data is continually recorded. The “bigdata” database of this disclosure includes both dose events and responseevents (compared to current healthcare databases that are weightedtoward response events) and the dose and response events are temporallycorrelated (compared to current healthcare databases). Temporalcorrelation can include time matching different sets of data streams.

“Big data” has been characterized by “four Vs”: Volume, Velocity,Variety and Veracity. In some examples, the automated dose-responserecord system 100 of this disclosure addresses each of thesecharacteristics in order to optimize the acquired data for “big data”use and analysis.

Volume—The more data you have the better it is. The automateddose-response record system 100 of this disclosure can maximize datavolume by collecting data not only from the physiologic monitors butalso from some or all of the OR equipment and other dose eventsincluding machine vision video observations. Velocity—The speed at whichyou process the data. The automated dose-response record system 100 ofthis disclosure can maximize data velocity by automatically recordingeverything which removes the human function that always slow processesdown. Variety—How different is the data. The automated dose-responserecord system 100 of this disclosure maximizes data variety by recordingmost if not all data sources in the OR or other care locations,including but not limited to: physiologic monitors, equipment,medication injections, fluids and video. Veracity—How accurate is thedata, the truthfulness of the data. The automated dose-response recordsystem 100 of this disclosure maximizes data veracity by automaticallyrecording the data without requiring human input. In some examples, theautomated dose-response record system 100 of this disclosure includesSensor Fusion, a data analytic system that monitors input data in orderto reject clearly mistaken inputs such as might occur if an EKG leadcomes lose for example improving the veracity of the database. In someexamples, Sensor Fusion may include a threshold-controlledartifact-removal module and/or a Kalman filter.

In some examples as shown in FIG. 2, module 201 of the automateddose-response record system 200 may consolidate a wide variety ofequipment used for anesthesia and surgery. Some of this equipment,including but not limited to: the physiologic monitors, the urine outputmonitor and the blood loss monitor, produce response event data that canbe automatically recorded by the automated dose-response record system200.

In some examples as shown in FIG. 2, module 201 of the automateddose-response record system 200 may consolidate a wide variety ofequipment that produce dose event data, including but not limited to:medication identification and measurement system 228 and the IV fluididentification and measurement system 230, gas flow meters, medicalequipment (e.g., 270) such as a mechanical ventilator, apneumoperitoneum insufflator and a electrosurgical generator—dose eventdata that can be automatically recorded by the automated dose-responserecord system 200 (e.g., dose event data can be received by processingcircuitry 157, 257 and stored on one or more storage devices).

The automated dose-response record system 100,200 can not onlyconsolidates various electrical and electromechanical equipment 270 butcan also consolidate the data outputs of the various equipment for easyelectrical communication with the processing circuitry 157, 257. Theconsolidation of various types of medical equipment 270 describedthroughout this disclosure in, on or off of the module 201 of theautomated dose-response record system 200 solves another practicalobstacle currently preventing an automated dose-response record.Currently, much of the equipment mentioned above does not producedigital data that documents the equipment's operation because thevarious equipment manufacturers have chosen not to provide output data.The practical solution is that the vender of the automated dose-responserecord system 200 can require that any equipment 270 that is to belocated in, on or in electrical communication with the module 201include data outputs and the vender can also prescribe the digitalformat. These benefits are not provided in any conventional system.

Machine vision cameras and software are good at measuring distances,movements, sizes, looking for defects, fluid levels, precise colors andmany other quality measurements of manufactured products. Machine visioncameras and software can also be “taught” through AI and ML to analyzecomplex and rapidly evolving scenes such as those in front of a cardriving down the road. Machine vision cameras and software don't getbored or distracted.

FIG. 12 illustrates an isometric view of another example module 1201including an automated dose-response system 1200 for generating anautomated electronic anesthetic record where the module can be easilylocated proximate to a patient. FIG. 12 can be similar to FIG. 2,therefore, for the sake of brevity all elements may not be described infurther detail. Like numbers may represent like elements. For example,the module 1201 including the automated dose-response record system 1200for generating an automated electronic anesthetic record can include anyof the features of the module 201 including automated dose-responserecord system 200 for generating an automated electronic anestheticrecord described herein. Further for example, the IV fluididentification and measurement system 230 can be the same or similar asIV fluid identification and measurement systems 230 of FIG. 2 describedherein. Likewise, an identification and measurement system 228 can bethe same or similar as identification and measurement system 228described herein. Processing circuitry 1257 and one or more storagedevices 1259 can include all the features of the processing circuitry157, 257 and the one or more storage devices 159, 259, and can includeother features described herein. Unless otherwise described, elementsperforming related functions can be the same or similar, or areinterchangeable throughout this disclosure.

In some examples as shown in FIG. 12, the automated dose-response recordsystem 1200 of this disclosure includes systems and methods for usingmachine vision cameras 1297A,B and software to “observe” the patient. Ifthe patient is in surgery, the patient's head may be the focus of theobservation. In some examples, during surgery the machine vision cameras1297A,B and software may be “looking” for (e.g., sending, detecting,monitoring) various dose events including but not limited to maskventilation, endotracheal intubation or airway suctioning. In otherwords, the machine vision cameras 1297A,B can generate and send doseevent data (e.g., information) to be received and analyzed by processingcircuitry 1257.

In some examples, during surgery the machine vision cameras 1297A,B andsoftware may be “looking” for (e.g., monitoring, sensing, detecting)response events including but not limited to movement, grimacing,tearing or coughing or changes in skin color or sweating. In otherwords, the machine vision cameras 1297A,B can generate and send responseevent information to be received and analyzed by processing circuitry1257. Movement, grimacing, tearing and coughing are all signs of “light”anesthesia and that the patient may be in pain. Subtle changes in skincolor from pinkish to blueish or grayish may indicate inadequateoxygenation or low perfusion. Subtle changes in skin color from pinkishto reddish may indicate hyperthermia or an allergic reaction. Sweatingmay indicate inadequate perfusion or hyperthermia. In any event,observing the patient is regarded by the American Society ofAnesthesiologists as the most basic of all monitors. Machine visioncameras 1297A,B and software do not get bored and can be programed torecognize subtle changes that may be missed by the human observer. Bothmovements and skin color changes may be subtle. The baseline color maybe very difficult for the observer to remember, whereas the machinevision cameras 1297A,B and software can precisely “remember” thebaseline color and recognize even subtle changes (e.g., response events)over time. In some examples, pain may be detected by facial expressionanalysis, such as by processing circuitry 1257 receiving response eventinformation from the machine vision cameras 1297A,B, analyzing suchresponse event data, and recording or displaying the response event dataor other information derived from the response event data, or alerting auser via a user or other personnel via a user interface, such as thedisplay 226 or the remote display 287.

In some examples, vital signs such as heart rate, respiration rate,blood oxygen saturation and temperature can be measured remotely viacamera-based methods. Vital signs can be extracted from the opticaldetection of blood-induced skin color variations—remotephotoplethysmography (rPPG). In some examples, this technique works bestusing visible light and Red Green Blue (RBG) cameras. However, it hasalso been shown to work using near-infrared light (NIR) and NIR cameras.Just like pulse oximetry, a well-known technology for detecting pulseand blood oxygen saturation, rPPG relies on the varying absorption ofdifferent wavelengths of light caused by blood volume changes and theoxygen saturation of the blood in the small blood vessels beneath theskin. Unlike pulse oximetry that needs to be in contact with the skin,rPPG enables contactless monitoring of human cardiac activities bydetecting the pulse-induced subtle color changes on the human skinsurface using a regular RGB camera.

In some examples, this disclosure anticipates automating the remotephotoplethysmography using techniques such as, but not limited to,region of interest (RoI) detection and full video pulse extraction(FVP). In some examples, this disclosure also anticipates using acombination of visible light and near-infrared light wavelengths todetect different parameters. In some examples, additional measurementsare anticipated using the rPPG technology including but not limited tomeasuring blood glucose and hemoglobin levels.

FIG. 13 illustrates an isometric view of yet another example module 1301including a system 1300 for generating an automated electronicanesthetic record located proximate to a patient. FIG. 13 can be similarto FIG. 1, therefore, for the sake of brevity all elements may not bedescribed in further detail. Like numbers may represent like elements.For example, the module 1301 including the automated dose-responserecord system 1300 for generating an automated electronic anestheticrecord can include any of the features of the modules 101, 201, 1201including automated dose-response record system 100, 200, 1200 forgenerating an automated electronic anesthetic record described herein.Further for example, the IV fluid identification and measurement system130 can be the same or similar as IV fluid identification andmeasurement systems 130 described herein. Likewise, an identificationand measurement system 128 can be the same or similar as identificationand measurement system 128 described herein. Processing circuitry 1357and one or more storage devices 1359 can include all the features of theprocessing circuitry 157, 257, 1257, 1502 and the one or more storagedevices 159, 259, 1259, 1504, 1506, 1516 and can include other featuresdescribed herein. Unless otherwise described, elements performingrelated functions can be the same or similar, or are interchangeablethroughout this disclosure.

In some examples as shown in FIG. 13, if the patient is on the ward, inthe nursing home or other long-term care facility or at home, the wholepatient may be the focus of the observation. In some examples, if thepatient is on the ward, in the nursing home or other long-term carefacility or at home the machine vision cameras 1397 and software may be“looking” for (e.g., sensing, monitoring, detecting) dose eventsincluding but not limited to repositioning the patient or suctioning theairway or assisting the patient out of bed or any other nursingprocedure.

In some examples, if the patient is on the ward, in the nursing home orother long-term care facility or at home, the machine vision cameras1397 and software may be “looking” (e.g., sensing, monitoring,detecting) for response events including but not limited to restlessnessor getting out of bed without assistance or coughing or changes in thebreathing pattern. Recent research has shown that machine vision cameras1397 and software with AI can recognize moods with reasonable accuracy.The patient's mood could be an important response event that can berecorded.

As shown in technique 2400 of FIG. 24, various operations can beperformed by the dose-response systems 100, 200, 1200, 1300 andsubsystems disclosed herein. While the technique 2400 can be performedby the dose-response systems 100, 200, 1200, 1300, the technique 2400can also be performed by other systems, and the systems 100, 200, 1200,1300 can perform other techniques In an example, a dose-response systemcan perform technique 2400 using processing circuitry and one or morestorage devices including a memory. The memory can have instructionsstored thereon, which when executed by the processing circuitry causethe processing circuitry to perform the operations. For example,operation 2402 can include receiving dose event data (e.g., a doseevent, dose information) from one or more dose sensors. Operation 2404can include receiving response event data (e.g., response event,response information) from one or more response sensors. The dose eventdata can include information corresponding to a dose provided to thepatient, and the response event data can include data corresponding to aresponse of the patient. Operation 2406 can include temporallycorrelating the dose event data and the response event data. Operation2408 can include saving the temporally correlated dose-response eventdata to at least one of the one or more storage devices, such as storagedevice 1516 of FIG. 15. Temporally correlating dose-response event datacan include continuously temporally correlating the dose-response eventdata, such as in a processor-based timer, in a beat-by-beat,second-by-second type manner, as opposed to the non-continuous, extendedintervals and less accurate methods of traditional medical practice. Insome examples, temporally correlating the dose-response event dataincludes temporally correlating the dose-response event data, such as ina range between about every 0.01 seconds to 15 minutes. In someexamples, it may be preferable to temporally correlate in a rangebetween every 0.1 seconds to 5 minutes. It may be more preferable totemporally correlate in a range between every 0.5 second to 1 minute. Itmay be even more preferable to correlate in a range between every 1second and 30 seconds, to maximize accuracy while not oversampling therate of doses and responses, however, any suitable temporal correlationmay be used to facilitate accurate, safe and meaningful correlationwhere a direct, time-based relationship between the dose and theresponse is captured. In some examples, the dose response event data canbe temporally correlated substantially continuously, such as is possiblein processor-based systems. Continuous can include data collection thatis persistent, consistent and without the errors of scheduled manualentry, result in producing a continuous, consistent data stream.

In some examples, operation 2410 can include displaying informationcorresponding to the dose-response event data. In operation 2412, if theprocessing circuitry detects a concerning response, the processingcircuitry can cause alerting a user to the response. Operation 2414 caninclude analyzing the temporally correlated dose-response event data. Insome examples, operation 2414 can include aggregating the temporallycorrelated dose-response event data with temporally correlateddose-response event data collected from other patients. In someexamples, operation 2414 can include aggregating the temporallycorrelated dose-response event data with temporally correlateddose-response information collected from the same patient over adifferent period of time. Comparing data from the same patient may allowa provider to detect when a patient develops a tolerance to a drug, suchas a pain killer. In an example, if the rate of grimacing by the patientincreases or they start to grimace sooner (e.g., response) after beinggiven a pain medication (dose), as the pain medication is given overdifferent days, weeks and months. Operation 2414 can also use orfacilitate ML. Operation 2416 can include “big data” analysis includingAI or ML. The one or more storage devices, which can include anelectronic record or database, can be configured to be accessed byartificial intelligence or machine learning algorithms to retrieve thetemporally correlated dose-response event and compare the temporallycorrelated dose-response event to other temporally correlateddose-response events across a population of patients and output big datacorrelation insights to at least one storage device or display. Data canpass back and forth between operations 2408, operation 2414 andoperation 2416 to analyze and understand dose-response events across apopulation of patients. In some examples, traditional mathematicalanalysis can be used with or instead of AI or ML, including evaluatingan average, median, range, mode, etc..

In technique 2400, the dose information can include data/eventsgenerated by one or more of: an RFID interrogator, a barcode reader, aQR reader, a machine vision digital camera, any combination thereof, orany other suitable sensor. The response information can includedata/events generated by a machine digital camera or any other suitablesensor. The response information can include an image of one or moremovements, secretions or skin color changes, and the processingcircuitry can be configured to identify changes in the responseinformation. In some examples the processing circuitry can use machinelearning to identify changes in the response information. In someexamples, the response information includes physiologic data generatedby a physiologic monitor (e.g., 270, urine output collection system242). For example, the physiologic data can include at least one of:electrocardiogram, pulse oximetry, blood pressure, temperature,end-tidal CO₂, expired gases, respiratory rate, hemoglobin, hematocrit,cardiac output, central venous pressure, pulmonary artery pressure,brain activity monitor, sedation monitor, urine output, blood loss,blood electrolytes, blood glucose, blood coagulability, train-of-fourrelaxation monitor data, IV extravasation monitor data and body weight,and any combination thereof or other suitable physiologic data.

Implementation of any of the techniques described herein may be done invarious ways. For example, these techniques may implemented in hardware,software, or a combination thereof. For a hardware implementation, theprocessing units may be implemented within on or more applicationspecific integrated circuits (ASICs), digital signal processors (DSPs),digital signal processing devices (DSPDs), programmable logic devices(PLDs), field programmable gate arrays (FPGAs),processors, controllers,micro-controllers, microprocessors, other electronic units designed toperform the functions described above, and/or a combination thereof

Furthermore, embodiments may be implemented by hardware, software,scripting languages, firmware, middleware, microcode, hardwaredescription languages, and/or any combination thereof. When implementedin software, firmware, middleware, scripting language, and/or microcode,the program code or code segments to perform the necessary tasks may bestored in a machine-readable medium such as a storage medium. A codesegment or machine-executable instruction may represent a procedure, afunction, a subprogram, a program, a routine, a subroutine, a module, asoftware package, a script, a class, or any combination of instructions,data structures, and/or program statements. A code segment may becoupled to another code segment or a hardware circuit by passing and/orreceiving information, data, arguments, parameters, and/or memorycontents. Information, arguments, parameters, data, etc. may be passed,forwarded, or transmitted via any suitable means including memorysharing, message passing, token passing, network transmission, etc.

For a firmware and/or software implementation, the techniques may beimplemented with modules (e.g., procedures, functions, and so on) thatperform the functions described herein. Any machine-readable mediumtangibly embodying instructions may be used in implementing thetechniques described herein. For example, software codes may be storedin a memory. Memory may be implemented within the processor or externalto the processor. As used herein the term “memory” refers to any type oflong term, short term, volatile, nonvolatile, or other storage mediumand is not to be limited to any particular type of memory or number ofmemories, or type of media upon which memory is stored.

There are two common modes for ML: supervised ML and unsupervised ML.Supervised ML uses prior knowledge (e.g., examples that correlate inputsto outputs or outcomes) to learn the relationships between the inputsand the outputs. The goal of supervised ML is to learn a function that,given some training data, best approximates the relationship between thetraining inputs and outputs so that the ML model can implement the samerelationships when given inputs to generate the corresponding outputs.Unsupervised ML is the training of an ML algorithm using informationthat is neither classified nor labeled, and allowing the algorithm toact on that information without guidance. Unsupervised ML is useful inexploratory analysis because it can automatically identify structure indata. Either of supervised ML or unsupervised ML can be used to trainthe systems described herein to correlate information from one or moresensors, such as a machine vision digital camera as having a particularmeaning. For example, either of supervised or unsupervised ML can beused to train the systems to correlate facial expressions with responseevents. The system can be trained to “read” a particular patient, or agroup of patients that may or may not include the particular patientbeing monitored.

Common tasks for supervised ML are classification problems andregression problems. Classification problems, also referred to ascategorization problems, aim at classifying items into one of severalcategory values (for example, is this object an apple or an orange?).Regression algorithms aim at quantifying some items (for example, byproviding a score to the value of some input). Some examples of commonlyused supervised-ML algorithms are Logistic Regression (LR), Naive-Bayes,Random Forest (RF), neural networks (NN), deep neural networks (DNN),matrix factorization, and Support Vector Machines (SVM).

Some common tasks for unsupervised ML include clustering, representationlearning, and density estimation. Some examples of commonly usedunsupervised-ML algorithms are K-means clustering, principal componentanalysis, and autoencoders.

FIG. 15 illustrates an example electronic and/or electromechanicalsystem 1500 of a medical system in accordance with some examplesdescribed herein. The system 1500 will be described with respect to themedical system 20, but can include any of the features described hereinto perform any of the methods or techniques described herein, forexample, by using the processor 1502. The processor can includeprocessing circuitry 157 or 257 of FIGS. 1 and 2. In some examples, theprocessing circuitry 1502 can include but is not limited to, electroniccircuits, a control module processing circuitry and/or a processor. Theprocessing circuitry may be in communication with one or more memory andone or more storage devices. A single processor can coordinate andcontrol multiple, or even all the aspects of the system 1500 (e.g., ofmodules 101, 201), or multiple processors can control all the aspects ofthe system 1500. In some examples the storage device 1516 or memory1504, 1506, 1516 can include at least a portion of the patient'sanesthetic record saved thereon. The system 1500 can also include any ofthe circuitry and electronic and/or electromechanical componentsdescribed herein, including but not limited to, any of the sensor(s)described herein (e.g., sensors 1521), such as but not limited to, RFIDbarcode or QR codes sensors, machine vision cameras, retinal scanners,facial recognition scanners, fingerprint readers, actuators and positionsensors described herein. Other sensors 1521 can include medicalequipment 270 such as a physiologic monitor or machine vision digitalcamera (1297A,1297B, 1397 of FIGS. 12 and 13) configured to take imagesof a patient 202 lying in a bed. The system 1500 may also include orinterface with accessories or other features such as any of: a remotedisplay or wireless tablet (e.g., 287, FIG. 2), as well as any of theother systems described herein.

The processing circuitry 1502 can receive information from the varioussensors described herein, make various determinations based on theinformation from the sensors, output the information or determinationsfrom the information for output on the display or wireless tablet,output instructions to provide an alert or an alarm, power variouscomponents, actuate actuators such as clamps and flow managing devices,etc., or alert another system or user, as described herein. For the sakeof brevity, select systems and combinations are described in furtherdetail above and in the example sets provided in the Notes and VariousExamples section below. Other embodiments are possible and within thescope of this disclosure.

Further, FIG. 15 illustrates generally an example of a block diagram ofa machine (e.g., of module 101, 201) upon which any one or more of thetechniques (e.g., methodologies) discussed herein may be performed inaccordance with some embodiments. In alternative embodiments, themachine 1500 may operate as a standalone device or may be connected(e.g., networked) to other machines. In a networked deployment, themachine 1500 may operate in the capacity of a server machine, a clientmachine, or both in server-client network environments. The machine1500, or portions thereof may include a personal computer (PC), a tabletPC, a personal digital assistant (PDA), a mobile telephone, a webappliance, a network router, switch or bridge, or any machine capable ofexecuting instructions (sequential or otherwise) that specify actions tobe taken by that machine. Further, while only a single machine isillustrated, the term “machine” shall also be taken to include anycollection of machines that individually or jointly execute a set (ormultiple sets) of instructions to perform any one or more of themethodologies discussed herein, such as cloud computing, software as aservice (SaaS), other computer cluster configurations.

Examples, as described herein, may include, or may operate on, logic ora number of components, modules, or like mechanisms. Such mechanisms aretangible entities (e.g., hardware) capable of performing specifiedoperations when operating. In an example, the hardware may bespecifically configured to carry out a specific operation (e.g.,hardwired). In an example, the hardware may include configurableexecution units (e.g., transistors, circuits, etc.) and a computerreadable medium containing instructions, where the instructionsconfigure the execution units to carry out a specific operation when inoperation. The configuring may occur under the direction of theexecution units or a loading mechanism. Accordingly, the execution unitsare communicatively coupled to the computer readable medium when thedevice is operating. For example, under operation, the execution unitsmay be configured by a first set of instructions to implement a firstset of features at one point in time and reconfigured by a second set ofinstructions to implement a second set of features.

Machine (e.g., computer system) 1500 may include a hardware processor1502 (e.g., processing circuitry 157, 257, a central processing unit(CPU), a graphics processing unit (GPU), a hardware processor core, orany combination thereof), a main memory 1504 and a static memory 1506,some or all of which may communicate with each other via an interlink(e.g., bus) 1508. The machine 1500 may further include a display unit1510, an alphanumeric input device 1512 (e.g., a keyboard), and a userinterface (UI) navigation device 1514 (e.g., a mouse). In an example,the display device 1510, an input device such as an alphanumeric inputdevice 1512 and UI navigation device 1514 may be a touch screen display.The display unit 1510 may include goggles, glasses, or other AR or VRdisplay components. For example, the display unit may be worn on a headof a user and may provide a heads-up-display to the user. Thealphanumeric input device 1512 may include a virtual keyboard (e.g., akeyboard displayed virtually in a VR or AR setting.

The machine 1500 may additionally include a storage device (e.g., driveunit) 1516, a signal generation device 1518 (e.g., a speaker), a networkinterface device 1520, and one or more sensors 1521, such as a globalpositioning system (GPS) sensor, compass, accelerometer, or othersensor. The machine 1500 may include an output controller 1528, such asa serial (e.g., universal serial bus (USB), parallel, or other wired orwireless (e.g., infrared (IR), near field communication (NFC), etc.)connection to communicate or control one or more peripheral devices oractuators of the system. Peripheral devices can include but are notlimited to any displays, controllers or memories in electricalcommunication with the system, and actuators can include but are notlimited to: one or more stop-flow clamps 1060A,B (FIG. 10) and one ormore flow rate clamps 1478 (FIG. 14) of the system.

The storage device 1516 may include a machine readable medium 1522 thatis non-transitory on which is stored one or more sets of data structuresor instructions 1524 (e.g., software) embodying or utilized by any oneor more of the techniques or functions described herein. Theinstructions 1524 may also reside, completely or at least partially,within the main memory 1504, within static memory 1506, or within thehardware processor 1502 during execution thereof by the machine 1500. Inan example, one or any combination of the hardware processor 1502, themain memory 1504, the static memory 1506, or the storage device 1516 mayconstitute machine readable media that may be non-transitory.

While the machine readable medium 1522 is illustrated as a singlemedium, the term “machine readable medium” may include a single mediumor multiple media (e.g., a centralized or distributed database, orassociated caches and servers) configured to store the one or moreinstructions 1524.

The term “machine readable medium” may include any medium that iscapable of storing, encoding, or carrying instructions for execution bythe machine 1500 and that cause the machine 1500 to perform any one ormore of the techniques of the present disclosure, or that is capable ofstoring, encoding or carrying data structures used by or associated withsuch instructions. Non-limiting machine-readable medium examples mayinclude solid-state memories, and optical and magnetic media. Specificexamples of machine readable media may include: non-volatile memory,such as semiconductor memory devices (e.g., Electrically ProgrammableRead-Only Memory (EPROM), Electrically Erasable Programmable Read-OnlyMemory (EEPROM)) and flash memory devices; magnetic disks, such asinternal hard disks and removable disks; magneto-optical disks; andCD-ROM and DVD-ROM disks.

The instructions 1524 may further be transmitted or received over acommunications network 1526 using a transmission medium via the networkinterface device 1520 utilizing any one of a number of transferprotocols (e.g., frame relay, internet protocol (IP), transmissioncontrol protocol (TCP), user datagram protocol (UDP), hypertext transferprotocol (HTTP), etc.). Example communication networks may include alocal area network (LAN), a wide area network (WAN), a packet datanetwork (e.g., the Internet), mobile telephone networks (e.g., cellularnetworks), Plain Old Telephone (POTS) networks, and wireless datanetworks (e.g., Institute of Electrical and Electronics Engineers (IEEE)802.11 family of standards known as Wi-Fi®, IEEE 802.16 family ofstandards known as WiMax®), IEEE 802.15.4 family of standards,peer-to-peer (P2P) networks, among others. In an example, the networkinterface device 1520 may include one or more physical jacks (e.g.,Ethernet, coaxial, or phone jacks) or one or more antennas to connect tothe communications network 1526. In an example, the network interfacedevice 1520 may include a plurality of antennas to wirelesslycommunicate using at least one of single-input multiple-output (SIMO),multiple-input multiple-output (MIMO), or multiple-input single-output(MISO) techniques. The term “transmission medium” shall be taken toinclude any intangible medium that is capable of storing, encoding orcarrying instructions for execution by the machine 1500, and includesdigital or analog communications signals or other intangible medium tofacilitate communication of such software.

Method examples described herein may be machine or computer-implementedat least in part. Some examples may include a computer-readable mediumor machine-readable medium encoded with instructions operable toconfigure an electronic device to perform methods as described in theexamples. An implementation of such methods may include code, such asmicrocode, assembly language code, a higher-level language code, or thelike. Such code may include computer readable instructions forperforming various methods. The code may form portions of computerprogram products. Further, in an example, the code may be tangiblystored on one or more volatile, non-transitory, or non-volatile tangiblecomputer-readable media, such as during execution or at other times.Examples of these tangible computer-readable media may include, but arenot limited to, hard disks, removable magnetic disks, removable opticaldisks (e.g., compact disks and digital video disks), magnetic cassettes,memory cards or sticks, random access memories (RAMs), read onlymemories (ROMs), and the like.

Some of the benefits of the automated dose-response record systems 100,200, 1200, 1300 and the subsystems described throughout this disclosure,and including the machine 1500, can include features to help withmonitoring medication, fluid and anesthesia delivery, as well asdocumenting medication, fluid and anesthesia delivery, as well as otherfunctions. In general, doctors and nurses are not interested inreplacing themselves and their jobs with automated drug delivery orautomated anesthesia systems. However, there is great interest inautomated record keeping. Virtually all healthcare providers wouldprefer the “old” paper record and a pen to the “new” computer records.Filling out the electronic medical record (EMR) using a computerkeyboard, mouse and various menus is widely viewed as a slow, cumbersomeand distracting process. The challenge with automated record keeping isautomating the data input that documents the numerous activities,anesthesia related events, fluid, gas and medication administration,ventilator settings, pressure off-loading effectiveness, as well asoutputs such as blood loss and urine output, that constitute ananesthetic experience.

A challenge in implementing the automated dose-response record systemand fluids 100, 200, 1200, 1300 with an automated electronic anestheticrecord (EAR) or electronic medical record (EMR) is to force as littlechange in the caregiver's routine as possible onto the clinicians usingthis system. Medical personnel tend to be creatures of habit andtradition and they generally do not like change. For example, IVmedications are traditionally administered from a syringe and the doseis determined by the caregiver observing the plunger moving relative toa scale printed on the syringe. Maintaining this general technique ofdrug administration may have the highest probability of acceptance byhealthcare users who are typically slow to embrace changes in theirroutine.

Further with regard to benefits of the modules, systems and machinesdescribed herein, the automated dose-response record system 200 ofmodule 201 can generate an automated electronic medical record (EMR)with the module 201 locatable proximate to the patient 202. The module201 can be a module for housing unrelated electronic andelectromechanical surgical equipment. The module 201 need notnecessarily be configured to house unrelated electronic andelectromechanical surgical equipment in all examples, and other modulescan include the system for generating an automated EMR.

The module 201 can be an automated EMR system that can include one ormore systems (e.g., 200, 228, 230) configured to measure (e.g., monitor)and record one or more of functions involved in a surgical anestheticenvironment, and can include life support functions. The one or moresystems 228, 230 can measure and record data automatically. However, insome examples, a user may initiate any of the systems described hereinto measure and/or record data. These various measurements may beelectronically recorded (such as on mass storage 1516 (FIG. 15) anddisplayed on the electronic anesthetic record display 226 (e.g., displaydevice 1510, FIG. 15). Inputs to the automated EMR system may be managedby the anesthetic record input component 224 (e.g., input device 1512;FIG. 15). The anesthetic record input component 224 (e.g., input device1512; FIG. 15) can include a touch-screen display 226 that organizes allof the inputs to the EMR into easily accessed and utilized information.In some examples, and as shown in FIG. 2, the identification andmeasurement system 228 of this disclosure may be located proximate thepatient 202. The control displays for the identification and measurementsystem 228 may include a dedicated display proximate the identificationand measurement system 228 or may be shared space on the anestheticrecord input component 224 or display 226. In these locations, theinformation and controls of the identification and measurement system228 can be viewed by the anesthesiologist or other user, in a singlefield of vision with the patient and surgical field.

Example methods of employing the systems, modules and machines disclosedherein are described throughout this disclosure and in the methods ofFIGS. 16-21 which are illustrative in nature. Other methods describedherein may also be performed by the systems, modules and machinesdescribed herein, and the systems modules and machines described hereinmay be used to perform other methods.

FIGS. 16-18 show flow charts illustrating techniques for identification,measurement, monitoring, security and safety related to medicationsand/or IV fluids. The methods may be used with the systems, sub-systemsand modules of FIGS. 1-15 (e.g., 101, 201, 1500), but may also be usedwith other systems. Likewise, the systems, subsystems of modules ofFIGS. 1-15 may also be used with other methods. The techniques 1600,1700, 1800, 1900, 2000, 2100, 2300 can be performed by at least onenon-transitory machine-readable medium (e.g., computer readable)including instructions for operation of the systems described herein.Some steps of techniques may be performed by a provider. The systems caninclude processing circuitry (e.g., 157, 257, 1500, including one ormore processors, processing circuitry hardware) for executing theinstructions. The instructions, when executed by the processingcircuitry can cause the processing circuitry to perform operationsdescribed in FIGS. 16-21 and 23, and as described in the examplesthroughout this disclosure.

FIG. 16 is a flow chart illustrating an example technique 1600 of IVfluid identification and measurement. To start the technique, inoperation 1602 a provider hangs an IV fluid bag and attached dripchamber on electronic scale hooks in an IV fluid identification andmeasurement unit (e.g., FIG. 14). In operation 1604, a machine visioncamera and software can identify the fluid and bag by the barcode labelon the IV fluid bag. In operation 1606, the machine vision camera andsoftware can identify the individual drops in the drip chamber andmeasure the size of the drop to determine the fluid volume per drop andcount the number of drops per unit time. In operation 1608 the machinevision camera and software can calculate the flow rate by multiplyingthe number of drops per unit time by the volume/drop. In operation 1610,the fluid flow rate is displayed and document in the EMR.

In operation 1612, if the machine vision camera and software fails toidentify individual drops in the drip chamber, in operation 1614 themachine vision camera and software can look for a floating ball (e.g.,float) that is located in the drip chamber to determine if the ball isfloating and if the ball is moving. In operation 1616, when the ball isnot floating and/or moving, IV clamps are closed and the provider canchange the empty IV bag if necessary. In operation 1618, if the machinevision camera and software can determine that the ball is floating andmoving, the system determines that the fluid flow is so fast that thefluid flow is constant or continuous such that individual drops cannotbe measured. In operation 1618, because individual drops cannot bedetermined, the system switches to measuring the fluid flow rate usingan electronic IV scale (FIG. 14) to determine the fluid flow rate. Inoperation 1620, the fluid flow rate can be determined by monitoring thechange in IV bag weight per time. In operation 1622, the fluid flow ratecan be displayed and documented in the EMR.

FIG. 17 is a second flow chart illustrating a technique 1700 includingaspects of the technique 1600 of IV fluid identification and measurementfrom the perspective of processing circuitry (e.g., 257, FIG. 2; 1502,FIG. 15). The technique 1700 may include an operation 1702 to receive IVfluid identification information from a first IV sensor (e.g., one ormore sensors), such as an RFID or barcode reader to identify the fluidor other characteristics of an IV fluid bag as described herein.Operation 1704 can include saving the IV identification information to astorage device (e.g., one or more storage devices, memory, EMR).Operation 1706 can include to receive fluid drop information from asecond IV sensor, such as a machine vision camera that detects, sensesand measures an individual drop in a drip chamber to determine a fluidvolume per drop and measure the number of drops per unit of time. Whilethe illustrative example of FIG. 17 includes the first IV sensor and thesecond IV sensor, in some examples the first IV sensor and the second IVsensor can be the same sensor or same one or more sensors. Operation1708 can include to determine if a fluid drop was recognized by thesecond IV sensor. If in operation 1708 it is determined that a fluiddrop was recognized, operation 1710 can include determining a fluid flowrate, such as by calculating the flow rate by multiplying the number ofdrops per unit time by the volume per drop. In some examples, the volumeper drop is measured, while in other examples the volume per drop may beinput by a user, or can be a value retrieved from a memory. Operation1712 can include transmitting instructions to a display to cause a fluidflow rate to be displayed. Operation 1714 can include saving flow rateinformation to the storage device to document the fluid flow rate in theEMR. Any time a change is input or detected in the system, updated flowrate information can be displayed and saved.

If in operation 1708 it is determined that a fluid drop was notrecognized, operation 1716 can include receiving float information fromthe second IV sensor or another IV sensor. The float information caninclude information about a float in the drip chamber including is thefloat still (e.g., not moving), moving, or is movement of the floatslowing down. Operation 1718 can include determining if the float ismoving. If the float is moving, Operation 1720 can include determiningthe fluid flow is constant. In such a scenario, the fluid is flowing butthe fluid is flowing so quickly that individual drops of fluid cannot bedistinguished because the fluid is flowing as a steady stream. Operation1720 can further include determining the fluid flow rate by receiving IVbag physical characteristic information from a physical characteristicsensor, such as a weight sensor. The physical characteristic informationcan include weight information from the weight sensor (e.g., scale).Operation 1722 can include determining the fluid flow rate bycalculating the change in IV bag weight over a period of time. Operation1726 can include saving flow rate information based on the determinedflow rate in operation 1722. Operation 1724 can include transmittinginstructions to cause the fluid flow rate to be displayed on a display(e.g., outputting the fluid flow rate to be displayed on a display). Inother examples, instead of weight information, the physicalcharacteristic information can include a position of the IV bag thatchanges as a result of a change in weight, without the physicalcharacteristic data corresponding directly to a weight measurement.Other physical characteristics and other physical characteristic sensorsconfigured to monitor IV fluid delivery may be provided such that anautomated, or at least partially automated EMR system is enabled.Technique 1700 can be repeated as needed until all medications aredelivered.

If in operation 1718 it is determined that the float is not moving,operation 1728 can include determining that no fluid is flowing from theIV bag and transmitting one or more of: an instruction an actuator suchas a clamp, to cause the actuator to inhibit fluid flow to the patient(e.g., close the clamp onto IV tubing to prevent flow); and transmit andinstruction to an indicator (e.g., display, audible, tactile indicator)to cause an alert to be generated. Operation 1730 can include saving ano fluid event to the storage device or displaying a no fluid event on adisplay.

FIG. 18 is a flow chart illustrating an example technique 1800 ofmedication identification and measurement. In operation 1802 a providerinserts a medication syringe into an injection portal (e.g., 411, FIG.4). In operation 1804 the medication can be identified by a sensor suchas by at least one of the RFID, barcode or QR sensors described herein.In operation 1806 processing circuitry checks for medication errors bycomparing the medication against one or more of: a doctor's orders,allergy history, medical history, other medications and current vitalsigns. In operation 1808, the results of the medication error check canbe displayed on an electronic record display. The results can indicateno error, the presence of an error, specific details about the error, orpresent a link to access information including additional details aboutthe error. In operation 1810, if a serious medication error isrecognized, the error deploys (e.g., causes actuation of) IV tubingclamps (e.g., 1060A, 1060B of FIG. 10) to prevent injection of themedication.

If in operation 1812, such as when no errors are determined, the machinevision camera and software can measure the diameter of the syringe. Inoperation 1814, an image of, or representation of the image of thesyringe, is displayed on the electronic record display. In operation1816 the provider squeezes the plunger of the syringe. In operation1818, the machine vision camera and software measure the distancetraveled by the syringe's plunger seal (e.g., 548, FIG. 5). In operation1820 the processing circuitry calculates the volume injected bymultiplying the syringe diameter times the distance of plunger travel.The processing circuitry can also calculate the dose by multiplying thevolume injected by the concentration of the medication. In operation1822 the injected dose and volume are displayed on the electronic recorddisplay. In operation 1824 the injected dose and volume are time stampedand recorded in the electronic medical record.

FIG. 19 is a second flow chart illustrating a technique 1900 includingaspects of the technique 1800 of medication identification andmeasurement from the perspective of processing circuitry (e.g., 157,FIG. 1; 257, FIG. 2; 1502, FIG. 15).

Technique 1900 can include an operation 1902 to receive medicationidentification information such as medication type, concentration,brand, lot number or amount, from a first medication sensor (e.g., RFID,barcode or QR reader). Operation 1904 can include saving medicationidentification information to a storage device (e.g., one or morestorage devices, memory). Operation 1906 can include comparingmedication identification information to at least one of a medicationorder, allergy history, medical history, other medications ordered forthe patient, and vital signs (e.g., previously obtained vital signs orcurrent vital signs of the patient via continuous monitoring). Operation1908 can include determining if a medication error is present. Operation1910 can include receiving syringe information from a second medicationsensor (e.g., a sensor configured to measure diameter, such as a machinevision camera). Operation 1912A can include receiving medicationdelivery information from the second medication sensor or anothermedication sensor. In some examples, the medication delivery informationcan include a distance of a syringe plunger travel.

Operation 1912B can include transmitting instructions to a display tocause an image of the syringe (e.g., actual image or representation ofthe syringe) to be displayed. A representation of the syringe caninclude an image communicating information about the syringe that is notan image of the actual syringe or can be a modified image of thesyringe, such as to highlight or point out aspects of the syringe ormedication within the syringe

Using the medication delivery information obtained in operation 1912A,operation 1914 can include determining a medication delivery amount.Operation 1916 can include transmitting instructions to a display (e.g.,display 226, FIG. 2) to cause the medication delivery information ormedication delivery amount to be displayed.

If in operation 1908 it is determined that a medication error ispresent, operation 1920 can include transmitting instructions includingerror information to the display or another display to cause the errorinformation to be displayed. In some examples, any of the instructionsdescribed herein that are sent to the display can be sent to one or moredisplays. Such displays can be located locally or remotely (e.g., in adifferent part of a room, in a separate room, in another building, inanother state, in another country), to alert multiple providers. Forexample, a provider such as a nurse anesthetist located adjacent to thepatient can be alerted to and provided with the information via display226. In addition, a second provider, such as an anesthesiologistsupporting the nurse anesthetist, and who may be supporting other nurseanesthetists working in different rooms, can also be alerted on adisplay of a mobile device, which may prompt them to check in with andpotentially assist the nurse anesthetist. This concept can be appliedoutside the operating room to manage medication delivered by providersworking in different rooms of a hospital or other care center, while asecond provider such as a nurse manager, nurse practitioner, pharmacistor doctor oversees the work of the first provider. In operation 1922 theerror information can be saved to one or more storage devices (e.g.,259, FIG. 2; 1516, FIG. 15).

Also in response to determining that a medication error has occurred inoperation 1908, operation 1924 can include transmitting instructions toan actuator such as an IV tubing clamp to inhibit (e.g., prevent,reduce, limit) injection. In some examples, the actuator can reduce orlimit the amount of the injection to a specified amount rather thancompletely inhibiting or preventing administration of the medication.Operation 1926 can include saving an inhibit injection event informationto a storage device, such as any of the one or more storage devices(e.g., 259, FIG. 2; 1516, FIG. 15). The inhibit injection eventinformation can include information such as the time of the event andthe action taken to inhibit injection and how much the injection wasinhibited (e.g., partially inhibited, completely inhibited, or amount ofmedication inhibited from injection).

If in operation 1908 it is determined that a medication error has notoccurred, operation 1910 can include receiving syringe informationincluding a syringe diameter from a sensor such as a machine visioncamera. In some examples, the sensor can be the first medication sensoror can be a second medication sensor. Operation 1912A can includereceiving medication delivery information from a sensor such as from thefirst medication sensor, the second medication sensor or another sensor.The medication delivery information can include a distance of plungertravel relative to a syringe body. Operation 1912B can includetransmitting instructions to one or more displays such as, display 226,FIG. 2, to cause an image of the syringe or representation of thesyringe to be displayed.

Operation 1914 can include determining a medication delivery amount,such as a volume or dose injected. For example, the volume injected canbe calculated by multiplying the syringe diameter by the distance ofplunger travel. The dose injected can be calculated by multiplying thevolume injected by the concentration of the medication.

Operation 1916 can include transmitting instructions to the one or moredisplays to cause the medication delivery information to be displayed.Operation 1918 can include saving medication delivery information to thestorage device (e.g., EMR). In some examples, the medication deliveryinformation can include, but is not limited to, volume, dose, time ofthe injection, or time period of the injection.

FIG. 20 is a flow chart illustrating an example of a second technique ofIV fluid identification and measurement including safety and securitymeasures. Aspects of technique 2000 can be similar or the same astechniques 1800 and 1900, however, technique 2000 is particularlywell-suited to the challenges of maintaining safety and security withcontrolled drugs such as narcotics. Technique 2000 can include operation2002 of identifying a medication (e.g., a controlled drug) andidentifying a health care provider, such as by RFID, barcode or QR codereader, retinal scanner, facial recognition, or fingerprint. Operation2002 can occur at the time a provider checks out a drug from a pharmacyor a medication dispensing machine. The medication can include anarcotic in a tamper-proof, non-refillable syringe.

Operation 2004 can include identifying a provider such as by RFID,barcode or QR code reader, retinal scanner, facial recognition, orfingerprint at a patient's bedside, such as at an injection portal(e.g., 411, FIG. 4). The provider can be the same or a differentprovider as the provider in operation 2002. In operation 2006, theprovider inserts the medication syringe into the patient's injectionportal. In operation 2008, the controlled drug is identified, such as byan RFID, barcode or QR code reader associated with the injection portal.Operation 2010 can include processing circuitry checking for medicationerrors by comparing the medication against doctor's orders, allergyhistory, medical history, other medications and vital signs. Operation2012 can include displaying medication error check results on a display,such as display 226, FIG. 2. If the medication error is of a seriousnature, the error can cause IV tubing clamps to prevent injection inoperation 2014. Operation 2016 can include machine vision camera andsoftware measuring the diameter of the syringe. Operation 2018 caninclude an image, or an image representing the syringe being displayedon a display, such as display 226, FIG. 2. Operation 2020 can include aprovider squeezing the plunger of the syringe. Operation 2022 caninclude the machine vision camera and software measuring the distancetraveled by the syringe's plunger seal (e.g., 548, FIG. 5). Operation2024 can include processing circuitry determining the volume ofmedication injected by multiplying the syringe diameter by the distanceof plunger travel or determining the dose of medication injected bymultiplying the volume of medication injected by the concentration ofthe medication. Operation 2026 can include displaying the injectedvolume or dose on a display, such as display 226, FIG. 2.

Operation 2028 can include saving the injected volume or dose along witha timestamp to the EMR. Operation 2030 includes repeating the operationsof technique 2000 as necessary until the machine vision camera andsoftware documents an empty syringe. Operation 2032 includes completingthe “chain of custody” for a specific syringe of controlled medication.The operations of technique 2000 can be repeated as necessary for othersyringes, thereby completing the “chain of custody” for each syringe.

FIG. 21 is a second flow chart illustrating a technique 2100 includingaspects of the technique 2000 of IV fluid identification and measurementincluding safety and security measures from the perspective ofprocessing circuitry, such as, but not limited to, processing circuitry157, FIG. 1; 257, FIG. 2; 1502, FIG. 15. The technique may involveprocessing circuitry 2202B, such as may be part of a medication vendingsystem 2200 as shown in FIG. 22. FIG. 22 illustrates generally anexample of a block diagram of vending system and a medication deliverysystem of FIGS. 1-21 and 23 upon which any one or more of the techniques(e.g., methodologies) discussed herein may perform in accordance withsome embodiments. FIGS. 21 and 22 are described together.

In some examples, operations 2102 and 2104 can be part of a vendingsystem (2202, FIG. 22) for managing medication withdrawal from apharmacy or other vending system. Operations 2110-2136 can be part of amedication delivery system (e.g., can be used with the bedside patientsystems and modules shown and describe in FIGS. 1-15; medicationdelivery system 2210, FIG. 22). Operation 2138 can tie information,including data generated by the vending system 2202 and the medicationdelivery system 2210 together to facilitate tracking a “chain ofcustody” for a specific syringe of controlled medication from thepharmacy until the medication is completely injected into the patient.Chain of custody information can be stored to one or more of: thevending system storage 2202A, the medication delivery storage 2216A, andchain of custody storage device (e.g., 2206, FIG. 22) and the EMR. Anyof the storage described herein can include one or more storage devicesor memory as described herein and can include other storage devices inelectrical communication with the vending system or the medicationdelivery system.

Operation 2102 of the vending system can include receiving withdrawingprovider identification information from a medication dispensing sensor2202C, such as a first RFID or barcode reader that reads a badge of aprovider and reads the medication identification information from asyringe or other medication container, or any other type of suitablesensor described herein. Operation 2104 can include associating andsaving the medication identification information and the withdrawingprovider identification information to a vending system storage device(e.g., 2202A, FIG. 22).

Operation 2110 can include receiving medication identificationinformation from a first identification sensor (e.g., RFID, QR, barcodereader, or machine vision camera reads information about a medication)and receiving delivery provider identification information from thefirst identification sensor or another identification sensor (e.g., asecond identification sensor, another RFID, QR or barcode reader,machine vision camera, retinal scanner, facial recognition sensor orfingerprint reader). In some examples, patient identificationinformation can also be obtained from one of the first identificationsensor, second identification sensor or another identification sensor,such as by scanning patient identification information on a hospitalwristband. In some examples receiving the medication identification, theprovider identification information or the patient identification cancause the processing circuitry to send an instruction to a display toprompt the user for the other of the medication identificationinformation, the provider identification information or the patientidentification information.

Operation 2112 can include comparing the received identificationinformation to one or more of: a medication order, allergy history,medical history, other medications and current vital signs. Operation2114 can include determining if a medication error is present. If it isdetermined that a medication error is present, operation 2116 caninclude transmitting instructions including error information to adisplay to cause the error information to be displayed. Operation 2118can include saving the error information to one or more storage devices.Further, if in operation 2114 it is determined that a medication errorhas occurred, operation 2120 can include transmitting inhibit injectioninstructions to an actuator such as , but not limited to, an IV tubingclamp (e.g., 1060A, 1060B; FIG. 10) to inhibit injection. Operation 2122can include saving an inhibit injection event information to one or morestorage devices.

Operation 2124 can include receiving syringe information from a secondmedication sensor (e.g., syringe diameter including syringe innerdiameter, outer diameter, or wall thickness from a machine visioncamera). Operation 2124 can include receiving syringe size informationfrom a data storage device, the syringe size information provided by thesyringe manufacturer that supplies the specific syringes used by thespecific healthcare facility. Operation 2126 can include transmittinginstructions to a display to cause an image of the syringe or arepresentation of the syringe to be displayed. Operation 2128 caninclude receiving syringe movement information from the secondmedication sensor or another sensor. Syringe movement information caninclude, for example, a distance of travel of the syringe plungerrelative to the syringe barrel.

Operation 2130 can include determining medication delivery informationbased on the syringe movement information. Medication deliveryinformation can include, for example, a volume or dose of medicationdelivered to the patient (e.g., ejected from the syringe). In someexamples, the volume of medication delivered (e.g., ejected from thesyringe) can be calculated by multiplying the syringe inner diameter bythe distance of plunger travel. Likewise, the dose of medicationdelivered can be calculated by multiplying the calculated volume by aconcentration of the medication. Operation 2132 can include savingmedication delivery information to one or more storage devices. In otherwords, operation 2132 can include documenting volume, dose and time inan EMR, in some cases automatically without intervention from aprovider.

Operation 2134 can include transmitting instructions to one or moredisplays described herein to cause the medication delivery informationto be displayed. Operation 2136 can include determining that a syringeis empty and saving “chain of custody” complete for the specific syringeof medication (e.g., controlled drug) to one or more storage devices.

To complete and document the chain of custody, thereby ensuring themedication was delivered to the patient, operation 2138 can include oneor more of receiving, associating and saving to one or more chain ofcustody storage devices (e.g., 2206, FIG. 22), information from both thepharmacy vending system 2202 (FIG. 22) and the bedside medicationdelivery system 2210 (FIG. 22)(e.g., 1516; FIG. 15). In some examplesthe one or more chain of custody storage devices or sensors is notnecessarily separate from the vending system storage 2202A or themedication delivery storage 2216A or sensors 2216B, but rather canreside with one or the other systems, a different system, multiplesystems or can be included as a single storage device.

FIG. 23 illustrates and example technique 2300 for assessingphysiological events. In some examples, the EMRs created by theautomated dose-response record system 100, 200, 400, 600, 800 canprovide the most accurate and temporally correlated information aboutthe relationship between any injected medication and the resultingphysiologic response. In some examples, this is uniquely accuratedose-response data can be used as a final check of the chain of custodyfor controlled medications or any medication. The processing circuitry157, 257 may include or be in electrical communication with artificialintelligence (AI) and/or machine learning that can compare the measuredphysiologic response in the several minutes after a medication isinjected, to the expected physiologic response for that dose of thatmedication. For example, if the injected medication was a narcotic, itwould be expected that the heart rate and blood pressure of the patientwould decrease quickly after the injection.

In some examples, if the expected physiologic response does not occur,the AI software of the automated dose-response record system 100, 200,400, 600, 800 may electronically “flag” that injection as suspicious.For example, if there is no physiologic response after injecting whatwas supposed to be a narcotic, it is possible that the drug had beenstolen and replaced by saline. On the other hand, no response may simplymean that the patient is addicted to and tolerant of narcotics and thattoo is worth noting. An unpredicted response does not prove anything butmultiple unpredicted responses in multiple patients can be suspicious.Therefore, aggregating or analyzing data over time for a particularpatient or provider can alert management to issues. If any individualprovider traverses a threshold number of flags (e.g., too many “flags”)for unexpected physiologic responses (including no response), theautomated dose-response record system 100, 200, 400, 600, 800 cangenerate an alert to notify management and an investigation of thatprovider may be warranted. Knowing that AI is “watching” the patients'response to a healthcare providers' injected medications, can be asignificant deterrent to tempted drug thieves.

Technique 2300 can include determining if one or more unexpectedphysiological events has occurred, analyzing saving, aggregating anddisplaying such information, in any order. The method can be performedby processing circuitry 157, 257, 1502, including other processingcircuitry, memories and databases in electrical communication withprocessing circuitry 157, 257, 1502 to one or more of: receivephysiologic data, analyze physiologic data, determine physiologic datais unexpected, create and send instructions to cause an alert to theprovider or another user, or save a physiological event information(e.g., data) to a storage device 1516 which may include a database. Thephysiological event information can include, but not limited to datagenerated by the various sensors and equipment described herein,including one more of: physiological information, patient information,provider information, medication information, time information, locationinformation, facility information, equipment information, aggregatedphysiological event information and analyzed physiologic eventinformation.

Operation 2302 can include receiving physiologic data from a physiologicsensor, Operation 2304 can include analyzing the physiologic data.Operation 2304 can include comparing the physiologic data to expectedphysiologic responses, such as the expected response based on the dose.Based on the outcome of the analysis in operation 2304, in operation2306, the processing circuitry can determine if the physiologic data isunexpected, and if so, operation 2308 can include saving unexpectedphysiologic event information to one or more storage devices, or caninclude sending instructions to one or more displays to displayunexpected physiologic event information.

Operation 2310 can include aggregating or analyzing physiologic eventinformation from a plurality of unexpected physiological events andgenerating aggregated or analyzed physiologic event information. In someexamples, aggregating can include aggregating a number of physiologicalevents by counting the number of physiological events for a givenprovider, patient, group of patients, medical facility, type ofmedication, or any other suitable assessment. Operation 2312 can includesaving aggregated or analyzed physiologic event information to one ormore storage devices or sending instructions to one or more displays todisplay aggregated or analyzed physiologic event information. In someexamples, the physiologic event information can include any type ofphysiologic event that occurs, including expected or desirablephysiologic events.

The operations of technique 2300 can help provide safer care forpatients, including providing narcotic medications when helpful, whilekeeping a close eye on drug abuse by providers or patients. Taken at ahigh level, technique 2300 can help medical facilities evaluate whichmedications are most often abused by patients or stolen by providers,and to mitigate risk for insurers.

Any operations of the various methods described herein can be used incombination with or separately from one another, depending on thedesired features and in consideration of constraints such as financial,space, material and manufacturing availability.

The above detailed description includes references to the accompanyingdrawings, which form a part of the detailed description. The drawingsshow, by way of illustration, specific embodiments in which theinvention can be practiced. These embodiments are also referred toherein as “examples.” Such examples can include elements in addition tothose shown or described. However, the present inventors alsocontemplate examples in which only those elements shown or described areprovided. Moreover, the present inventors also contemplate examplesusing any combination or permutation of those elements shown ordescribed (or one or more aspects thereof), either with respect to aparticular example (or one or more aspects thereof), or with respect toother examples (or one or more aspects thereof) shown or describedherein.

In this document, the terms “a” or “an” are used, as is common in patentdocuments, to include one or more than one, independent of any otherinstances or usages of “at least one” or “one or more.” In thisdocument, the term “or” is used to refer to a nonexclusive or, such that“A or B” includes “A but not B,” “B but not A,” and “A and B,” unlessotherwise indicated. In this document, the terms “including” and “inwhich” are used as the plain-English equivalents of the respective terms“comprising” and “wherein.” Also, in the following claims, the terms“including” and “comprising” are open-ended, that is, a system, device,article, composition, formulation, or process that includes elements inaddition to those listed after such a term in a claim are still deemedto fall within the scope of that claim. Moreover, in the followingclaims, the terms “first,” “second,” and “third,” etc. are used merelyas labels, and are not intended to impose numerical requirements ontheir objects. The terms approximately, about or substantially aredefined herein as being within 10% of the stated value or arrangement.

The above description is intended to be illustrative, and notrestrictive. For example, the above-described examples (or one or moreaspects thereof) may be used in combination with each other. Otherexamples can be used, such as by one of ordinary skill in the art uponreviewing the above description. The Abstract is provided to allow thereader to quickly ascertain the nature of the technical disclosure. Itis submitted with the understanding that it will not be used tointerpret or limit the scope or meaning of the claims. Also, in theabove Detailed Description, various features may be grouped together tostreamline the disclosure. This should not be interpreted as intendingthat an unclaimed disclosed feature is essential to any claim. Rather,inventive subject matter may lie in less than all features of aparticular disclosed example. Thus, the following claims are herebyincorporated into the Detailed Description as examples or examples, witheach claim standing on its own as a separate example, and it iscontemplated that such examples can be combined with each other invarious combinations or permutations. The scope of the invention shouldbe determined with reference to the appended claims, along with the fullscope of equivalents to which such claims are entitled.

NOTES AND VARIOUS EXAMPLES

Each of these non-limiting examples may stand on its own, or may becombined in various permutations or combinations with one or more of theother examples. The examples are supported by the preceding writtendescription as well as the drawings of this disclosure.

Example Set A

Example 1 is an automated dose-response record system including a modulefor housing waste-heat producing electronic and electromechanicalmedical equipment including at least one physiologic monitor, andincluding a system to measure and record administration of one or moreIV medications or fluids for IV administration via one or more of asyringe or IV tubing, the automated dose-response record systemcomprising: a housing configured to house the waste heat-producingelectronic and electromechanical medical equipment; a cowling thatsubstantially confines waste heat generated by the waste heat-producingelectronic and electromechanical medical equipment; a barcode reader oran RFID interrogator configured to identify at least one of the one ormore IV medications or fluids; processing circuitry in electricalcommunication with the barcode reader or an RFID interrogator and the atleast one physiologic monitor; and a machine vision digital camera inelectrical communication with the processing circuitry configured todetermine a volume of medication administered from a syringe or fluidadministered from an IV bag through an IV drip chamber into an IV tubingbased on an image generated by the machine vision digital camera,wherein the processing circuitry is configured to receive dose datagenerated by the machine vision digital camera and to determine thevolume of medication administered from a syringe or fluid administeredfrom an IV bag through an IV drip chamber into an IV tubing constitutinga dose event, wherein the processing circuitry is configured to receiveresponse data generated by the at least one physiologic monitorconstituting a response event, and wherein the processing circuitry isconfigured to temporally correlate the dose event and the response eventand automatically save the temporally-correlated dose-response event toan electronic record or database.

In Example 2, the subject matter of Example 1 includes, an injectionportal including an injection port that is configured to be in fluidcommunication with the IV tubing; and one or more orienting membersconfigured to guide syringes of varying diameters through the injectionportal to mate with the injection port.

In Example 3, the subject matter of Example 2 includes, wherein thesystem to measure and record the administration of the one or more IVmedications or fluids further comprises: a display in electricalcommunication with the machine vision digital camera, wherein themachine vision digital camera is configured to capture an image of asyringe when the syringe is inserted inside the injection portal, andwherein the display is configured to output a visual image orrepresentation of the syringe.

In Example 4, the subject matter of Examples 2-3 includes, wherein themachine vision digital camera is located to capture an image of aninside of the injection portal, and wherein the processing circuitry isconfigured to interpret the image of a syringe when the syringe isinserted into the injection portal to measure the volume of medicationinjected from the syringe by determining a size and an internal diameterof the syringe and measuring a distance a plunger of the syringe movesto calculate an injected volume.

In Example 5, the subject matter of Examples 1-4 includes, expiredgases, respiratory rate, hemoglobin/hematocrit, cardiac output, centralvenous pressure, pulmonary artery pressure, brain activity monitor,sedation monitor, urine output, blood loss, blood electrolytes, bloodglucose, blood coagulability, train-of-four relaxation monitor, IVextravasation monitor and body weight or any combination thereof.

In Example 6, the subject matter of Examples 1-5 includes, wherein theprocessing circuitry includes artificial intelligence or machinelearning algorithms that compare the response event to the temporallycorrelated dose event and provide immediate feedback via a display oralert device.

In Example 7, the subject matter of Examples 1-6 includes, wherein theelectronic record or database is configured to be accessed by artificialintelligence or machine learning algorithms to retrieve the temporallycorrelated dose-response event and compare the temporally correlateddose-response event to other temporally correlated dose-response eventsacross a population of patients and output big data correlation insightsto at least one storage device or display.

In Example 8, the subject matter of Examples 1-7 includes, a secondmachine vision digital camera to capture an image of a patient, whereinthe second machine vision digital camera is in electrical communicationwith the processing circuitry and wherein the processing circuitry isconfigured to analyze the image of the patient to identify an imagechange including a change in one or more of: a movement, a secretion askin color change, or any combination thereof.

In Example 9, the subject matter of Example 8 includes, wherein theresponse event can include one or more of: the movement, the secretion,the skin color change, or any combination thereof identified by theprocessing circuitry.

In Example 10, the subject matter of Examples 8-9 includes, wherein oneor more of: the image, the movement, the secretion, the skin colorchange, or any combination thereof are automatically saved to theelectronic record or database.

Example 11 is an automated dose-response record system including amodule for housing waste-heat producing electronic and electromechanicalmedical equipment including at least one physiologic monitor, andincluding a system to measure, temporally correlate and record dose andresponse events, the automated dose-response record system comprising: ahousing configured to house the electronic and electromechanical medicalequipment; a cowling that substantially confines waste heat generated bythe electronic and electromechanical medical equipment; and processingcircuitry in electrical communication with the electronic andelectromechanical medical equipment to receive dose digital data; andwherein the dose digital data is automatically delivered to theprocessing circuitry, constituting a dose event, and wherein theprocessing circuitry is in electrical communication with the at leastone electronic physiologic monitor to receive response digital dataconstituting a response event, wherein the processing circuitry isconfigured to temporally correlate the dose event and the response eventand automatically save the temporally-correlated dose-response event toan electronic record or database.

In Example 12, the subject matter of Example 11 includes, expired gases,respiratory rate, hemoglobin/hematocrit, cardiac output, central venouspressure, pulmonary artery pressure, brain activity monitor, sedationmonitor, urine output, blood loss, blood electrolytes, blood glucose,blood coagulability, train-of-four relaxation monitor, IV extravasationmonitor and body weight or any combination thereof.

In Example 13, the subject matter of Examples 11-12 includes, whereinthe electronic and electromechanical medical equipment includes one ormore of: a manual ventilator, a mechanical ventilator, an anesthesiamachine, a pneumoperitoneum insufflator, patient warming devices,medication infusion pumps, fluid infusion pumps, blood and fluidwarmers, electrosurgical units, continuous airway pressure device, bedand surgical table tilt controls, sequential compression device controlsand pressure off-loading air mattress controls or any combinationthereof.

In Example 14, the subject matter of Examples 11-13 includes, whereinthe processing circuitry includes artificial intelligence or machinelearning algorithms that can compare the response event to thetemporally correlated dose event and provide immediate feedback via adisplay or alert device.

In Example 15, the subject matter of Examples 11-14 includes, whereinthe electronic record or database is configured to be accessed byartificial intelligence or machine learning algorithms to retrieve thetemporally correlated dose-response event and compare the temporallycorrelated dose-response event to other temporally correlateddose-response events across a population of patients and output big datacorrelation insights to at least one storage device or display.

Example 16 is an automated dose-response record system comprising: ahousing configured to house waste heat-producing electronic andelectromechanical medical equipment including an electronic physiologicmonitor; a cowling that substantially confines the waste heat generatedby the waste heat-producing electronic and electromechanical medicalequipment; a system for monitoring administration of one or more IVmedications and fluids, the system comprising: at least one of a sensorconfigured to identify the one or more IV medications or fluids, or aninput configured to receive an identity of the one or more IVmedications or fluids; a machine vision digital camera to capture animage of one or more of a syringe or a drip chamber; processingcircuitry operably coupled to the sensor to receive an identity of oneor more IV medications or fluids, the processing circuitry operablycoupled to the machine vision digital camera to receive the capturedimage and determine a volume of medication administered from a syringeor fluid administered from an IV fluid bag based on the image, whereinthe processing circuitry is configured to automatically output theidentity and determined volume of medication administered from thesyringe or fluid administered from the IV bag to an electronic record ordatabase reflecting dose event data, and wherein the processingcircuitry is configured to receive a response event data generated bythe electronic physiologic monitor, wherein the dose event data and theresponse event data are temporally correlated by the processingcircuitry and are recorded into an electronic record or database.

In Example 17, the subject matter of Example 16 includes, a system tomeasure and record the administration of the one or more IV medicationsor fluids via one or more of a syringe or IV tubing, the system furthercomprising: an injection portal including an injection port that isconfigured to be in fluid communication with the IV tubing; and one ormore orienting members configured to guide syringes of varying diametersthrough the injection portal to mate with the injection port.

In Example 18, the subject matter of Examples 16-17 includes, aninjection portal including an injection port that is configured to be influid communication with IV tubing; and a display in electricalcommunication with the machine vision digital camera, wherein themachine vision digital camera is configured to capture an image of asyringe when the syringe is inserted inside the injection portal, andwherein the display is configured to output a visual image orrepresentation of the syringe.

In Example 19, the subject matter of Examples 16-18 includes, aninjection portal including an injection port that is configured to be influid communication with IV tubing; and wherein the machine visiondigital camera is located to capture an image of an inside of theinjection portal, and wherein the processing circuitry is configured tointerpret the image of a syringe when the syringe is inserted into theinjection portal to measure the volume of medication injected from thesyringe by determining a size and an internal diameter of the syringeand measuring a distance a plunger of the syringe moves to calculate aninjected volume.

In Example 20, the subject matter of Examples 16-19 includes, expiredgases, respiratory rate, hemoglobin/hematocrit, cardiac output, centralvenous pressure, pulmonary artery pressure, brain activity monitor,sedation monitor, urine output, blood loss, blood electrolytes, bloodglucose, blood coagulability, train-of-four relaxation monitor, IVextravasation monitor and body weight or any combination thereof.

In Example 21, the subject matter of Examples 16-20 includes, whereinthe processing circuitry includes artificial intelligence or machinelearning algorithms that can compare the response event data to thetemporally correlated dose event data and provide immediate feedback viaa display or alert device.

In Example 22, the subject matter of Examples 16-21 includes, whereinthe electronic record or database is configured to be accessed byartificial intelligence or machine learning algorithms to retrieve thetemporally correlated dose-response event data and compare thetemporally correlated dose-response event data to other temporallycorrelated dose-response event data across a population of patients andoutput big data correlation insights to at least one storage device ordisplay.

In Example 23, the subject matter of Examples 16-22 includes, whereinthe system to measure and record the administration of the one or moreIV medications or fluids further comprises: a hanger configured toreceive the IV bag; an electronic scale in electrical communication witha processor, wherein the hanger is configured to support the IV bag; anda float located in the IV drip chamber, wherein the machine visiondigital camera is located adjacent to the IV drip chamber, and whereinthe processing circuitry is configured to determine a volume of fluidflowing from the IV bag by determining a size of drops and a number ofthe drops per unit time to calculate a fluid flow rate, wherein theelectronic scale is configured to measure a combined weight of the IVbag, an IV drip chamber, IV tubing and fluid in the IV bag, and whereinthe processing circuitry is configured to determine a reduction in themeasured combined weight over time to determine a weight of the IVfluids infused over time and convert the measured combined weight overtime to at least one of a fluid flow rate or infused fluid volume,wherein at higher flow rates, when the drops in the IV drip chambercoalesce into a fluid stream that is un-interpretable by the machinevision camera and processing circuitry, the fluid stream causes a floatin the IV drip chamber to move indicating that fluid is flowing, andwherein when the system fails to identify individual drops and detectsthat the float is moving, the processing circuitry is configured tomeasure a fluid flow rate by determining a reduction of the combinedweight of the IV bag, the IV drip chamber, the IV tubing and the fluidin the IV bag over time.

Example 24 is an automated dose-response record system comprising: ahousing configured to house waste heat-producing electronic andelectromechanical medical equipment including an electronic physiologicmonitor; a cowling that substantially confines waste heat generated bythe waste heat-producing electronic and electromechanical medicalequipment; a system for monitoring administration of one or more IVmedications and fluids, the system comprising: at least one of a sensorconfigured to identify the one or more IV medications or fluids, or aninput configured to receive an identity of the one or more IVmedications or fluids; a machine vision digital camera to capture animage of one or more of a syringe or a drip chamber; processingcircuitry operably coupled to the sensor to receive the identity of theone or more IV medications or fluids, the processing circuitry operablycoupled to the machine vision digital camera to receive the capturedimage and determine a volume of medication administered from the syringeor fluid administered from an IV bag based on the image, wherein theprocessing circuitry automatically outputs the identity and determinedvolume of medication administered from the syringe or fluid administeredfrom an IV bag to an electronic record or database constituting a doseevent; and a machine vision digital camera to capture an image of apatient, wherein the machine vision digital camera is in electricalcommunication with the processing circuitry, wherein the machine visioncamera and the processing circuitry analyzes the image of the patient toidentify one or more of a movement, a secretion and a skin color changeconstituting a response event, and wherein the dose event and theresponse event are temporally correlated by the processing circuitry andautomatically recorded into an electronic record or database.

In Example 25, the subject matter of Example 24 includes, wherein themachine vision camera and processing circuitry are configured to analyzean image of a patient's head during a surgical procedure to identifyimage changes that include one or more movements including: grimacing,coughing, secreting, lacrimation, sweating, drooling, skin color change,or any combination thereof.

In Example 26, the subject matter of Examples 24-25 includes, whereinthe machine vision camera is located to capture the image of the patientin a bed and wherein the processing circuitry is configured to identifyimage changes that include one or more: movements includingrestlessness, trying to get out of bed without assistance, coughing, arocking breathing pattern indicative of an airway obstruction; asecretion including, lacrimation, sweating, drooling; or skin colorchanges indicative of inadequate oxygen, poor perfusion, hypothermia, orany combination of the movements, secretions or skin color changesthereof.

In Example 27, the subject matter of Examples 24-26 includes, whereinthe processing circuitry includes artificial intelligence or machinelearning algorithms that compare the response event to the temporallycorrelated dose event and provide immediate feedback via a display oralert device.

In Example 28, the subject matter of Examples 24-27 includes, whereinthe electronic record or database is configured to be accessed byartificial intelligence or machine learning algorithms to retrieve thetemporally correlated dose-response event and compare the temporallycorrelated dose-response event to other temporally correlateddose-response events across a population of patients and output big datacorrelation insights to at least one storage device or display.

In Example 29, the subject matter of Examples 24-28 includes, whereinthe processing circuitry analyzes the image of a head of the patientduring surgery to identify therapeutic interventions provided by ahealthcare provider including one or more of: mask ventilation,pharyngeal airway placement, endotracheal intubation and extubation,airway suctioning and eye taping, or any combination thereof, andwherein a result of the analysis is entered into the electronic recordor database as the dose event.

In Example 30, the subject matter of Examples 24-29 includes, whereinthe machine vision processing circuitry analyzes the image of thepatient in bed to identify therapeutic interventions from a healthcareprovider including one or more of: checking on the patient,repositioning the patient, administering medications, suctioning thepatient's airway or any combination thereof, and wherein a result of theanalysis is saved to the electronic record or database as the doseevent.

Example 31 is at least one machine-readable medium includinginstructions that, when executed by processing circuitry, cause theprocessing circuitry to perform operations to implement of any ofExamples 1-30.

Example 32 is an apparatus comprising means to implement of any ofExamples 1-30

Example 33 is a system to implement of any of Examples 1-30.

Example 34 is a method to implement of any of Examples 1-30.

Example Set B

Example 1 is a dose-response medical system comprising: processingcircuitry; and one or more storage devices including a memory, thememory including instructions which when executed on the processingcircuitry cause the processing circuitry to perform operationsincluding: receiving dose information and response information from oneor more sensors, wherein the dose information includes, datacorresponding to a dose provided to a patient, and wherein the responseinformation includes data corresponding to a response of the patient;and temporally correlating the dose information and the responseinformation and saving the temporally correlated dose-responseinformation to at least one of the one or more storage devices.

In Example 2, the subject matter of Example 1 includes, whereintemporally correlating the dose-response information includescontinuously temporally correlating the dose-response information.

In Example 3, the subject matter of Examples 1-2 includes, whereintemporally correlating the dose-response information includes temporallycorrelating the dose-response information in a range between every 0.1seconds to 15 minutes.

In Example 4, the subject matter of Examples 1-3 includes, aggregatingthe temporally correlated dose-response information with temporallycorrelated dose-response information collected from other patients.

In Example 5, the subject matter of Examples 1-4 includes, aggregatingthe temporally correlated dose-response information with temporallycorrelated dose-response information collected from the patient over adifferent period of time.

In Example 6, the subject matter of Examples 1-5 includes, wherein thedose information includes data generated by one or more of: an RFIDinterrogator, a barcode reader, a QR code reader, a machine visiondigital camera, or any combination thereof

In Example 7, the subject matter of Examples 1-6 includes, wherein theresponse information includes data generated by a machine vision digitalcamera.

In Example 8, the subject matter of Examples 1-7 includes, wherein theresponse information includes an image of the patient and wherein theprocessing circuitry is configured to image changes that include one ormore: movements including restlessness, trying to get out of bed withoutassistance, coughing, a rocking breathing pattern indicative of anairway obstruction; a secretion including, lacrimation, sweating,drooling; or skin color changes indicative of inadequate oxygen, poorperfusion, hypothermia, or any combination of the movements, secretionsor skin color changes thereof.

In Example 9, the subject matter of Examples 1-8 includes, wherein theresponse information includes an image of one or more of a movement, asecretion or a skin color change, and wherein the processing circuitryis configured to identify changes in the response information.

In Example 10, the subject matter of Examples 1-9 includes, wherein theresponse information includes physiologic data generated by aphysiologic monitor.

In Example 11, the subject matter of Example 10 includes, expired gases,respiratory rate, hemoglobin, hematocrit, cardiac output, central venouspressure, pulmonary artery pressure, brain activity monitor, sedationmonitor, urine output, blood loss, blood electrolytes, blood glucose,blood coagulability, train-of-four relaxation monitor data, IVextravasation monitor data and body weight.

In Example 12, the subject matter of Examples 1-11 includes, wherein theprocessing circuitry includes artificial intelligence or machinelearning algorithms that can analyze the temporally correlateddose-response information and output feedback on a display or cause analert to be activated.

In Example 13, the subject matter of Examples 1-12 includes, wherein theprocessing circuitry is configured to output to a display at least aportion of the temporally-correlated dose-response information.

In Example 14, the subject matter of Examples 1-13 includes, an analysissystem configured to receive the temporally correlated dose-responseinformation and to compare the temporally correlated dose-responseinformation to other temporally correlated dose-response informationacross a population of patients and to output a correlation orcomparison to at least one of the one or more storage devices or adisplay.

Example 15 is at least one machine-readable medium includinginstructions that, when executed by processing circuitry, cause theprocessing circuitry to perform operations to implement of any ofExamples 1-14.

Example 16 is an apparatus comprising means to implement any of Examples1-14.

Example 17 is a system to implement any of Examples 1-14.

Example 18 is a method to implement any of Examples 1-14.

What is claimed is:
 1. A module for housing waste-heat producingelectronic and electromechanical medical equipment including anautomated dose-response record system, at least one physiologic monitorand at least one machine vision camera, the module comprising: a housingconfigured to house waste heat-producing electronic andelectromechanical medical equipment; a cowling that substantiallyconfines waste heat generated by the waste heat-producing electronic andelectromechanical medical equipment; and the automated dose-responserecord system comprising: at least one machine vision camera positionedto detect at least one of dose events or response events, at least onephysiologic monitor to detect response events, and processing circuitryin electrical communication with the at least one machine vision cameraand the at least one physiologic monitor; wherein the processingcircuitry is configured to receive dose data generated by the machinevision digital camera constituting a dose event, the processingcircuitry is configured to receive response data generated by the atleast one physiologic monitor or machine vision digital cameraconstituting a response event, and the processing circuitry and softwareis configured to timestamp both the dose event and response event dataand automatically store the time-stamped data in memory, an electronicrecord or database allowing artificial intelligence analysis of thetemporally correlated dose event and the response event data.
 2. Theautomated dose-response record system of claim 1, wherein the processingcircuitry and software analyze the image of a head of the patient duringsurgery to identify therapeutic interventions provided by a healthcareprovider constituting dose events including one or more of: maskventilation, pharyngeal airway placement, endotracheal intubation andextubation, and airway suctioning, or any combination thereof, andwherein a result of the analysis is timestamped and entered into theelectronic record or database as a dose event.
 3. The automateddose-response record system of claim 1, wherein the processing circuitryand software analyze the image of the patient in bed to identifytherapeutic interventions from a healthcare provider constituting doseevents including one or more of: checking on the patient, repositioningthe patient, administering medications, suctioning the patient's airway,feeding the patient or any combination thereof, and wherein a result ofthe analysis is timestamped and saved to the electronic record ordatabase as a dose event.
 4. The automated dose-response record systemof claim 1, wherein the machine vision camera, processing circuitry andsoftware are configured to analyze an image of a patient's head during asurgical procedure to identify image changes constituting responseevents that include one or more of: grimacing, coughing, lacrimation,sweating, skin color change, or any combination thereof, and wherein aresult of the analysis is timestamped and entered into the electronicrecord or database as a response event.
 5. The automated dose-responserecord system of claim 1, wherein the machine vision camera is locatedto capture the image of the patient in a bed and wherein the processingcircuitry and software is configured to identify image changesconstituting response events that include one or more of movements thatinclude at least one of restlessness, trying to get out of bed withoutassistance, coughing, a rocking breathing pattern indicative of anairway obstruction; a secretion including, lacrimation, sweating,drooling; or skin color changes indicative of inadequate oxygen, poorperfusion, hypothermia, any combination of the movements, and secretionsor skin color changes, and a result of the analysis is timestamped andentered into the electronic record or database as a response event. 6.The automated dose-response record system of claim 1, wherein theelectronic physiologic monitor includes or measures one or more of thefollowing response events: electrocardiogram, pulse oximetry, bloodpressure, temperature, end-tidal CO₂, expired gases, respiratory rate,hemoglobin/hematocrit, cardiac output, central venous pressure,pulmonary artery pressure, brain activity monitor, sedation monitor,urine output, blood loss, blood electrolytes, blood glucose, bloodcoagulability, train-of-four relaxation monitor, IV extravasationmonitor and body weight or any combination thereof, and wherein a resultof the analysis is timestamped and entered into the electronic record ordatabase as a response event.
 7. The automated dose-response recordsystem of claim 1, wherein the processing circuitry and software includeartificial intelligence or machine learning algorithms that can comparethe time-stamped response event data to the temporally correlatedtimestamped dose event data and provide immediate point of care clinicaldecision support feedback via a display or alert device.
 8. Theautomated dose-response record system of claim 1, wherein the electronicrecord or database is configured to be accessed by artificialintelligence or machine learning algorithms to retrieve the temporallycorrelated dose-response event data and compare the temporallycorrelated dose-response event data to other temporally correlateddose-response event data across a population of patients and output bigdata correlation insights to at least one storage device or display. 9.The automated dose-response record system of claim 1, wherein theelectronic and electromechanical medical equipment includes one or moreof: a manual ventilator, a mechanical ventilator, an anesthesia machine,gas flow meters, a pneumoperitoneum insufflator, patient warmingdevices, medication infusion pumps, fluid infusion pumps, blood andfluid warmers, electrosurgical units, continuous airway pressure device,bed and surgical table tilt controls, sequential compression devicecontrols and pressure off-loading air mattress controls or anycombination thereof, and wherein the operational data from theelectronic and electromechanical medical equipment is timestamped andentered into the electronic record or database as a dose event.
 10. Anautomated dose-response record system, including a module for housingelectronic and electromechanical medical equipment including at leastone physiologic monitor and at least one machine vision digital camera,and including a system to measure, timestamp and record dose andresponse events, the automated dose-response record system comprising: ahousing configured to house electronic and electromechanical medicalequipment; a cable and hose management system located on a patient sideof the module, wherein the patient side of the module is configured toface a patient and provide the closest and most direct access to thepatient; at least one machine vision camera positioned to detect atleast one of dose events or response events; and processing circuitry inelectrical communication with the electronic and electromechanicalmedical equipment and machine vision digital camera to receive doseevent digital data, the processing circuitry in electrical communicationwith the at least one electronic physiologic monitor and machine visiondigital camera to receive response event digital data, wherein theprocessing circuitry and software is configured to timestamp both thedose event and response event data and automatically store thetimestamped data in memory, an electronic record or database allowingartificial intelligence analysis of the temporally correlated dose eventand a response event data.
 11. The automated dose-response record systemof claim 10, wherein the processing circuitry and software analyze theimage of a head of the patient during surgery to identify therapeuticinterventions provided by a healthcare provider constituting dose eventsincluding one or more of: mask ventilation, pharyngeal airway placement,endotracheal intubation and extubation, airway suctioning and eyetaping, or any combination thereof, and wherein a result of the analysisis timestamped and entered into the electronic record or database as adose event.
 12. The automated dose-response record system of claim 10,wherein the processing circuitry and software analyze the image of thepatient in bed to identify therapeutic interventions from a healthcareprovider constituting dose events including one or more of: checking onthe patient, repositioning the patient, administering medications,suctioning the patient's airway, feeding the patient or any combinationthereof, and wherein a result of the analysis is timestamped and savedto the electronic record or database as a dose event.
 13. The automateddose-response record system of claim 10, wherein the machine visioncamera, processing circuitry and software are configured to analyze animage of a patient's head during a surgical procedure to identify imagechanges constituting response events that include one or more of:grimacing, coughing, secreting, lacrimation, sweating, skin colorchange, or any combination thereof, and wherein a result of the analysisis timestamped and entered into the electronic record or database as aresponse event.
 14. The automated dose-response record system of claim10, the machine vision camera is located to capture the image of thepatient in a bed and wherein the processing circuitry and software isconfigured to identify image changes constituting response events thatinclude one or more of movements that include at least one ofrestlessness, trying to get out of bed without assistance, coughing, arocking breathing pattern indicative of an airway obstruction; asecretion including, lacrimation, sweating, drooling; or skin colorchanges indicative of inadequate oxygen, poor perfusion, hypothermia,any combination of the movements, and secretions or skin color changes,and a result of the analysis is timestamped and entered into theelectronic record or database as a response event.
 15. The automateddose-response record system of claim 10, wherein the electronicphysiologic monitor includes or measures one or more of the followingresponse events: electrocardiogram, pulse oximetry, blood pressure,temperature, end-tidal CO₂, expired gases, respiratory rate,hemoglobin/hematocrit, cardiac output, central venous pressure,pulmonary artery pressure, brain activity monitor, sedation monitor,urine output, blood loss, blood electrolytes, blood glucose, bloodcoagulability, train-of-four relaxation monitor, IV extravasationmonitor and body weight or any combination thereof, and wherein a resultof the analysis is timestamped and entered into the electronic record ordatabase as a response event.
 16. The automated dose-response recordsystem of claim 10, wherein the processing circuitry and softwareinclude artificial intelligence or machine learning algorithms that cancompare the timestamped response event data to the temporally correlatedtimestamped dose event data and provide immediate point of care clinicaldecision support feedback via a display or alert device.
 17. Theautomated dose-response record system of claim 10, wherein theelectronic record or database is configured to be accessed by artificialintelligence or machine learning algorithms to retrieve the temporallycorrelated dose-response event data and compare the temporallycorrelated dose-response event data to other temporally correlateddose-response event data across a population of patients and output bigdata correlation insights to at least one storage device or display. 18.The automated dose-response record system of claim 10, wherein theelectronic and electromechanical medical equipment includes one or moreof: a manual ventilator, a mechanical ventilator, an anesthesia machine,gas flow meters, a pneumoperitoneum insufflator, patient warmingdevices, medication infusion pumps, fluid infusion pumps, blood andfluid warmers, electrosurgical units, continuous airway pressure device,bed and surgical table tilt controls, sequential compression devicecontrols and pressure off-loading air mattress controls or anycombination thereof, and wherein the operational data from theelectronic and electromechanical medical equipment is timestamped andentered into the electronic record or database as a dose event.
 19. Anautomated dose-response record system that includes at least onephysiologic monitor and machine vision digital camera, and includes asystem to measure, timestamp and record dose and response events, theautomated dose-response record system comprising: at least one machinevision camera positioned to detect at least one of dose events orresponse events; processing circuitry in electrical communication withthe machine vision digital camera to receive dose event digital data; atleast one physiologic monitor to detect response events; and theprocessing circuitry is also in electrical communication with the atleast one electronic physiologic monitor and the machine vision digitalcamera to receive response event digital data, wherein the processingcircuitry and software is configured to timestamp both the dose eventand response event data and automatically store the timestamped data inmemory, an electronic record or database allowing artificialintelligence analysis of the temporally correlated dose event and aresponse event data.
 20. The automated dose-response record system ofclaim 19, wherein the processing circuitry and software analyze theimage of a head of the patient during surgery to identify therapeuticinterventions provided by a healthcare provider constituting dose eventsincluding one or more of: mask ventilation, pharyngeal airway placement,endotracheal intubation and extubation, airway suctioning and eyetaping, or any combination thereof, and wherein a result of the analysisis timestamped and entered into the electronic record or database as adose event.
 21. The automated dose-response record system of claim 19,wherein the processing circuitry and software analyze the image of thepatient in bed to identify therapeutic interventions from a healthcareprovider constituting dose events including one or more of: checking onthe patient, repositioning the patient, administering medications,suctioning the patient's airway, feeding the patient or any combinationthereof, and wherein a result of the analysis is timestamped and savedto the electronic record or database as a dose event.
 22. The automateddose-response record system of claim 19, wherein the machine visioncamera, processing circuitry and software are configured to analyze animage of a patient's head during a surgical procedure to identify imagechanges constituting response events that include one or more of:grimacing, coughing, secreting, lacrimation, sweating, skin colorchange, or any combination thereof, and wherein a result of the analysisis timestamped and entered into the electronic record or database as aresponse event.
 23. The automated dose-response record system of claim19, wherein the machine vision camera is located to capture the image ofthe patient in a bed and wherein the processing circuitry and softwareis configured to identify image changes constituting response eventsthat include one or more of movements that include at least one ofrestlessness, trying to get out of bed without assistance, coughing, arocking breathing pattern indicative of an airway obstruction; asecretion including, lacrimation, sweating, drooling; or skin colorchanges indicative of inadequate oxygen, poor perfusion, hypothermia,any combination of the movements, and secretions or skin color changes,and a result of the analysis is timestamped and entered into theelectronic record or database as a response event.
 24. The automateddose-response record system of claim 19, wherein the electronicphysiologic monitor includes or measures one or more of the followingresponse events: electrocardiogram, pulse oximetry, blood pressure,temperature, end-tidal CO₂, expired gases, respiratory rate,hemoglobin/hematocrit, cardiac output, central venous pressure,pulmonary artery pressure, brain activity monitor, sedation monitor,urine output, blood loss, blood electrolytes, blood glucose, bloodcoagulability, train-of-four relaxation monitor, IV extravasationmonitor and body weight or any combination thereof, and wherein a resultof the analysis is timestamped and entered into the electronic record ordatabase as a response event.
 25. The automated dose-response recordsystem of claim 19, wherein the processing circuitry and softwareinclude artificial intelligence or machine learning algorithms that cancompare the timestamped response event data to the temporally correlatedtimestamped dose event data and provide immediate point of care clinicaldecision support feedback via a display or alert device.
 26. Theautomated dose-response record system of claim 25, wherein theprocessing circuitry and software can report the point of care clinicaldecision support feedback to a remote display or alert device for remotesupervision or consultation.
 27. The automated dose-response recordsystem of claim 25, wherein the processing circuitry and software areconfigured to report the point of care clinical decision supportfeedback to a central monitoring station that includes the nurses'station.
 28. The automated dose-response record system of claim 19,wherein the electronic record or database is configured to be accessedby artificial intelligence or machine learning algorithms to retrievethe temporally correlated dose-response event data and compare thetemporally correlated dose-response event data to other temporallycorrelated dose-response event data across a population of patients andoutput big data correlation insights to at least one storage device ordisplay.
 29. The automated dose-response record system of claim 19,wherein the electronic and electromechanical medical equipment includesone or more of: a manual ventilator, a mechanical ventilator, ananesthesia machine, gas flow meters, a pneumoperitoneum insufflator,patient warming devices, medication infusion pumps, fluid infusionpumps, blood and fluid warmers, electrosurgical units, continuous airwaypressure device, bed and surgical table tilt controls, sequentialcompression device controls and pressure off-loading air mattresscontrols or any combination thereof, and wherein the operational datafrom the electronic and electromechanical medical equipment istimestamped and entered into the electronic record or database as a doseevent.
 30. The automated dose-response record system of claim 19,wherein the machine vision camera is located to capture the image of thepatient in a bed and wherein the processing circuitry and software isconfigured to identify image changes in remote photoplethysmography(rPPG) which relies on the varying absorption of different wavelengthsof light caused by blood volume changes and the oxygen saturation of theblood in the small blood vessels beneath the skin to determine bloodoxygen saturation.